What's inside the guide?

Data governance is becoming operational: teams need reusable ownership models, quality signals, access controls, and AI evidence that help daily work instead of living in static policy documents.

Operating patterns covered

  • A lightweight ownership model for products, domains, standards, and reviewable decisions.
  • How data contracts, lineage, and quality checks can reduce downstream surprise before changes ship.
  • Ways to connect AI system evidence with traditional data governance evidence.
  • How to turn documentation work into searchable, auditable operating context.

Use this guide as a planning aid when you are shaping governance workflows, prioritizing metadata work, or connecting AI oversight to your existing data platform.