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What Is a Database Schema? | 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 stewardshiprelational databasedata modelingIBM Privacy StatementGo to episodeRead the Data Leader's guide to learn how you can make your organization's data AI-ready.Webinar | On demand AI Agents run on data - is yours ready? Your data is your competitive edge. Learn how to unlock it securely and drive measurable ROI from AI in this short webinar. Watch nowTechsplainers Podcast Data management explained Techsplainers by IBM breaks down the essentials of data for AI, from key concepts to real‑world use cases. Clear, quick episodes help you learn the fundamentals fast. Listen nowEbook Unify and access your data to help scale your AI Learn why the path to AI-ready data often starts with effective access to both structured and unstructured data and the challenges that can impede data leaders. Read the ebookCase study Legal overhead turned into strategic insight Learn how an AI-powered legal agent helps accelerate decision-making, reduce manual work and improve compliance. Read the case studyVideo AI Academy: Building a data strategy for enterprise AI In this episode, Cathy Reese explains how organizations today need a data strategy that’s ready for advanced AI, which will require them to harness their highest quality data assets. Watch the episodeEbook The hybrid, open data lakehouse for AI Simplify data access and automate data governance. Discover the power of integrating a data lakehouse strategy into your data architecture, including cost-optimizing your workloads and scaling AI and analytics, with all your data, anywhere. Read the ebookReport Cost of a Data Breach Report 2025 Data breach costs have hit a new high. Get up-to-date insights into cybersecurity threats and their financial impacts on organizations. Read the reportGuide The data leader’s guide to AI-ready data Understand the actionable steps data leaders can take to overcome data challenges, establish the groundwork for a trusted data foundation and help get your organization’s data ready for AI. Read the guideReport How the C-suite is turning information into impact Explore insights from 1,700 CDOs in this cross-industry report for data leaders. Read the reportDiscover watsonx.dataDiscover data management solutionsExplore data and AI consulting servicesDiscover watsonx.dataExplore data management solutions

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