Data Provenance Standards: A Live Session on Implementation with IBM, Cisco, Blue Street Data, and more
Recorded session | January 28, 2026
Every data-driven decision carries risk if you can’t prove where the data came from—or how it changed.
In this live session from the OASIS Data Provenance Standards (DPS) Technical Committee, experts break down why data provenance has become a non-negotiable requirement for trust, transparency, and accountability in modern data ecosystems—especially as AI systems and privacy regulations raise the stakes.
You’ll see how provenance supports responsible AI, strengthens privacy controls, and creates measurable ROI through improved governance and operational clarity, capped with a real-world use case demonstrating scalability in action.
What you’ll learn:
What Data Provenance Really Is: A clear, practical definition—and why it’s foundational to AI trust and data privacy.
Standards in Motion: An overview of emerging technical standards and the goals behind OASIS DPS.
Implementation Without Disruption: How to introduce provenance into existing data environments without re-architecting everything.
From Compliance to ROI: A live use case showing how provenance drives measurable business value at scale.
Hear from the Experts: Live Q&A with practitioners shaping the future of provenance standards.
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