Data Governance Fundamentals

Who owns which data, who can access it, and how quality and compliance are enforced across an organization.

What it is

Data governance defines ownership, access policy, and quality standards for an organization's data — the rules layer that keeps data trustworthy and compliant as more teams produce and consume it.

Key points

Data ownership: every dataset needs an accountable owner — without one, quality issues have nowhere to be routed and no one to fix them.
Access policy: governance defines who can see what (especially PII and sensitive data), enforced technically via row/column-level security — a governance decision, implemented as an access-control mechanism.
Data classification: tagging data by sensitivity (public, internal, confidential, PII) is what makes automated policy enforcement possible at all — you can't apply a rule to data that isn't labeled.
Governance is a balance — too little leads to untrustworthy, non-compliant data; too much creates approval bottlenecks that push teams toward ungoverned shadow pipelines.