Governed Data Products for Cloud Migration and Trusted AI
Webinar Speaker: Donald Farmer, Research Fellow
Date: Monday, September 23, 2026
Time: 9:00 a.m. PT / 12:00 p.m. ET
It's a demanding time for data teams. Enterprises are migrating core business applications, such as ERP systems, to the cloud, and AI is maturing from pilot projects into real-world, impactful business processes. Leaders expect measurable returns on those investments. Yet recent TDWI research suggests that most organizations doubt their data is ready for AI, and regulators increasingly look for evidence of how automated decisions are produced.
When teams migrate, they discover data whose quality, ownership, and meaning no one recorded. Those who treat the move as an infrastructure exercise carry those unknowns forward; every AI model trained on migrated data inherits them. Someone must decide what to move, what to repair, and what to retire; no team reviews every record by hand.
Organizations now apply AI to both sides of this problem. Migration teams use machine learning to generate quality rules, harvest lineage, and flag anomalies as records move from source to destination; governance teams package the migrated data as data products: documented, quality-checked, and assigned to named owners, ready for AI teams to reuse.
In this webinar, TDWI research fellow Donald Farmer is joined by Tudor Borlea of Collibra and by Bastian Finkel and Stuart Giles of SAP. The panel will draw on hands-on experience, current research, and enterprise examples to show how governance turns a deadline-driven migration into a lasting foundation of governed data products for AI.
Attendees will learn:
- Why cloud migration is a governance event, not only an infrastructure project
- How governance needs differ across system conversion, new implementation, and selective data transition
- Where automation genuinely helps: AI-assisted rule generation, anomaly detection, and automated lineage harvesting
- How to publish migrated data as governed data products for reuse in AI initiatives
- What separates organizations that arrive AI-ready from those that relocate their problems