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 stewardshipCole StrykerTim MucciGDPRIBM Privacy Statementdata securitybusiness analyticsERPCRMsupply chain managementrelational databaseWatch all episodes of Mixture of ExpertsFDA’s draft guidanceISO 13485FINRA’s initiativesCloud storage databasedata lineageSpotifyApple PodcastsFind more episodesTim MucciCole StrykerEbook
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.
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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.
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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
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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.
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Streamlining and evolving fraud investigations with AI
Discover how Cogniware leverages AI solutions from IBM to drive efficiency in the financial crime space.
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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.
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How the C-suite is turning information into impact
Explore insights from 1,700 CDOs in this cross-industry report for data leaders.
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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.
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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.
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