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What Is a Data Mesh? | IBM

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WelcomeOverviewModern data stackAI-ready dataAI data managementDataOps frameworkOverviewStructured vs. unstructured dataMetadata managementDatasetsOverviewOverviewSQLPrimary keyNoSQL databasesOLTPVector databasesDatabase as a service (DBaaS)CAP theoremDatabase schemaMongoDBPostgreSQLRedisElasticsearchetcdCassandraApache HBaseCouchDBPrestoEntity relationship diagramOverviewOverviewData martOverviewDelta lakeApache icebergAWS data lake formationOverviewCloud data lake, data warehouse and data martMaster data management (MDM)OverviewData fabricData meshData modelingOverviewData acquisitionDirected acyclic graphData cleaningData reconciliationData validationData enrichmentData wranglingData virtualizationData automationFile transferData migrationStreaming dataOverviewETLELTChange data captureReal-time data integrationOverviewData ingestionOLAPStream processingUnstructured data processingOverviewOverviewHDFSMapreduceApache AvroApache RangerOverviewChief Data Officer (CDO)OverviewData literacyData marketplaceData modernizationData reductionData silosData strategyData SLAOverviewOverviewData accuracyData integrityData reliabilityOverviewData observabilityBad dataDark dataOverviewData stewardshipAlexandra JonkerAlice Gomstyndata architecturedatadata storagedata lakesdata warehousesdata platformssilosmicroservicesdata sharingdata qualitydata-driven decision-makingbig data machine learning artificial intelligence IBM Data Differentiatorpipelinesself-service data infrastructuredata-as-a-productgovernancedata productmetadataproduct developmentinteroperableDeep dive: What is a data product?IBM Privacy Statementdata engineeringextract, transform, loadextract, load, transformdata-as-a-productapplication programming interfacesdata integrationdata sciencedata lineageWatch all episodes of Mixture of ExpertsData fabricsilosdata managementautomationdata ingestionLearn more about the differences between data fabric and data meshdemocratizationreal-time datastreamingprocessingcloudscale storage and compute resourcesdebtschemaaccess controlsUS Health Insurance Portability and Accountability Actcurated datasetsBI initiativesdata visualizationsChatbotsvirtual agentscustomer experiencemodelsEbook Four steps to better business forecasting with analytics Use the power of analytics and business intelligence to plan, forecast and shape future outcomes that best benefit your company and customers. Read the ebookEbook 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 ebookInsights From data chaos to AI clarity: Activating AI through high-quality enterprise data Understand how focusing on well-governed, secure and collaborative access to data at scale empowers enterprises to maximize their AI investments Read the insightsAI in Action podcast Decision intelligence: Thoughtful, data-driven choices Learn how data intelligence helps leaders make sense of data, use generative AI wisely and make decisions based on what truly matters. Watch the episodeCase study Streamlining and evolving fraud investigations with AI Discover how Cogniware leverages AI solutions from IBM to drive efficiency in the financial crime space. Read the case studyWebinar | On demand Turning data strategy into AI impact Discover how to scale AI with a strong data foundation, deliver explainable and governed outcomes, and apply real-world lessons to your own AI roadmap. Watch nowReport 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 reportEbook 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 ebookInsights 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 insightsDiscover watsonx.dataDiscover data management solutionsDiscover analytics servicesDiscover watsonx.dataExplore data management solutionsData Mesh Principles and Logical Architecture

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