Definition: Data governance is the framework of policies, roles, standards and controls that determines how an organization's data is owned, defined, secured, accessed and used throughout its life.
Data ownership and stewardship, a shared business glossary and data catalog, classification of sensitive data, access policies, retention rules, lineage that shows where data came from, and quality standards with clear accountability.
Models inherit the problems of their data. Governance tells AI teams which data they may use for training or retrieval, how to handle personal information through steps like PII redaction, and how to trace an output back to its sources. It is the data foundation that AI governance builds on.
Good programs automate controls in the platform, such as role-based access in the warehouse, tags on sensitive columns and lineage captured by pipelines, rather than relying on manual sign-offs. Domain-owned approaches like data mesh pair local ownership with shared global rules.
Ryz data engineers implement catalogs, access controls and lineage in Snowflake, Databricks and cloud warehouses, working on your team.
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