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DESCRIPTION:Click for Latest Location Information: http://dgiq-aigov2026.da
 taversity.net/sessionPop.cfm?confid=166&proposalid=16846\nAs data and AI or
 ganizations accelerate their AI initiatives, many discover that model perfo
 rmance is ultimately limited by the quality, reliability, and context of th
 e data that powers it. Building AI-ready data requires more than modern pla
 tforms and pipelines—it demands a disciplined approach to data qualit
 y, lineage, observability, and governance across increasingly complex hybri
 d environments.\n\nThis session explores the foundational capabilities requ
 ired to transform enterprise data into a trusted asset for AI. Attendees wi
 ll learn from example how leading organizations are leveraging data contrac
 ts, observability frameworks, lineage tracking, and contextual, automated m
 etadata to improve trust, accelerate adoption, and reduce operational risk.
  The discussion will focus on practical strategies for creating data ecosys
 tems that are not only AI-ready but also provide tangible methods for contr
 ols.\n\nAttendees will learn how to:\n\n
 Approach scaling data quality and reliability for AI and production workloa
 ds\n
 Establish automated end-to-end lineage and traceability across distributed 
 systems\n
 Implement data contracts to create predictable and trustworthy data product
 s\n
 Leverage data observability to proactively detect quality, drift, and pipel
 ine issues\n
 Enrich data with business context and metadata to improve AI outcomes\n
DTSTART:20261117T134500
SUMMARY:From Data Products to AI Products: Building AI-Ready Data Foundatio
 ns
DTEND:20261117T142959
LOCATION: See Description
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