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What Is Data Processing? | IBM

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WelcomeOverviewModern data stackAI-ready dataAI data managementOverviewDataOps frameworkDataOps architectureOverviewStructured vs. unstructured dataMetadata managementDatasetsOverviewOverviewSQLPrimary keyNoSQL databasesOLTPVector databasesRAG vector databasesDatabase as a service (DBaaS)CAP theoremDatabase schemaMongoDBPostgreSQLRedisElasticsearchOpenSearchetcdCassandraApache HBaseCouchDBPrestoQuery optimizationEntity relationship diagramOverviewOverviewData martOverviewDelta lakeApache icebergAWS data lake formationOverviewFeature storeCloud data lake, data warehouse and data martMaster data management (MDM)OverviewData fabricData meshData modelingOverviewAgentic AI data engineeringData acquisitionOverviewData pipeline automation10 steps for automating data pipelinesDirected acyclic graphData cleaningData reconciliationData validationData enrichmentData wranglingData virtualizationData automationData orchestrationFile transferData migrationStreaming dataOverviewETLELTChange data captureReal-time data integrationCloud data integrationAI data integrationOverviewData contractData integration techniques and methodsOverviewData retrievalData ingestionOLAPStream processingUnstructured data processingReal-time data streamingOverviewOverviewHDFSMapreduceApache AvroApache RangerOverviewChief Data Officer (CDO)OverviewData literacyData marketplaceData optimizationData modernizationData reductionData silosData strategyData SLAData fragmentationOverviewData quality managementOverviewData accuracyData integrityData reliabilityOverviewData observabilityBad dataDark dataDirty dataAI data qualityOverviewData stewardshipTom KrantzAlexandra Jonkerdatastoragedatasetscentral processing unitsautomationartificial intelligencethe IBM Institute for Business Valuemachine learningparallel computingcloud computingIBM Privacy StatementIoTApache SparkSQLbatch jobsingestionforecastingrisk managementdata warehousesdata lakescloud computingGeneral Data Protection RegulationData visualizationdata storagegenerative AI Watch all episodes of Mixture of ExpertsApache Hadoop Sparksupply chainApache Kafkarecommendation engines.latencyedge computinginventory managementQuantum computingcryptographylow-latencydata engineersdata analyticsuser behavior analyticsredundanciesUnity Software50,000 timeslineagepipelinedata sovereigntysecuritydata minimizationencryptionWebinar | On demand Bridging the data engineering skills gap Watch the webinar to get an exclusive look at three IBM watsonx.data integration authoring styles and the innovation driving our roadmap. Watch the webinarWebinar | On demand Bridging the data engineering skills gap Watch the webinar to get an exclusive look at three IBM watsonx.data® integration authoring styles and the innovation driving our roadmap. Watch nowInsights Unleash the power of AI for seamless data integration Understand why organizations need to adopt a unified approach that lets them manage the full spectrum of integration capabilities from a single pane of glass, eliminating the need to rely on numerous tools. Read the insightsReport Unlock the value of real-time streaming data for AI Explore how to modernize your data stack, eliminate costly delays and build a future-ready foundation for both AI and everyday operations. Read the reportReport IBM named a leader in the 2025 Gartner® Magic Quadrant™ for Data Integration Tools Access the full report to learn why IBM is recognized as a Leader and how IBM watsonx.data integration helps organizations reduce complexity, improve data quality and accelerate time-to-insight. Read the reportExplore watsonx.data integrationDiscover data integration solutionsDiscover analytics servicesExplore IBM watsonx.data integrationExplore data integration solutionsWorldwide IDC Global DataSphere Forecast, 2024–2028: AI Everywhere, But Upsurge in Data Will Take Time2023 State of Data Science ReportDLA Piper GDPR Fines and Data Breach Survey: January 2025, DLA Piper

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