Catalog & Cocktails: The Honest, No-BS Data Podcast TAKEAWAY - All things Data Lineage with Dr. Irina Steenbeek
Jan 28, 2026
Practical realities of implementing data lineage, from when it helps and when it is overkill. How lineage untangles spaghetti systems to aid impact analysis and root-cause work. The overlap between data, lineage, and AI governance and why organizational factors often trump technical ones. Advice on focusing lineage efforts around use cases and necessary quality.
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Shared Foundations Across Governance
- Data governance, data lineage, and AI governance share a common foundation across people, processes, and technology.
- Irina Steenbeek found they overlap more than she initially expected, so treat them as related disciplines.
Lineage Is More Than Technology
- Data lineage spans technical, logical, business, and process levels and requires organizational capabilities.
- Technology alone won’t solve lineage; focus on people, processes, and proving metadata correctness.
Prioritize Lineage By Use Case
- Don’t try to capture lineage for everything; it’s often infeasible and wastes resources.
- First define use cases, required quality, and who will use and validate the metadata.
