Glossary
Metadata management
The discipline of capturing, organizing, and maintaining data about data so it can be found, trusted, and used consistently.
Also called: metadata governance
Metadata management is the ongoing practice of capturing, organizing, and maintaining "data about data": the names, definitions, types, ownership, lineage, and usage rules attached to an organization's tables, columns, reports, and models. It turns a warehouse full of tables into something a person or a tool can search, understand, and trust without asking the team that built it.
Metadata splits into overlapping kinds: technical metadata (schemas, types, data lineage), business metadata (definitions held in a business glossary), and operational metadata (job run times, freshness, quality scores). A data catalog is the tool most organizations use to store and surface all three, searchable by name, owner, or tag. This differs from a plain data dictionary, which documents structure alone; metadata management is the broader, ongoing program that keeps that documentation current as systems change.
It matters because undocumented data slows every downstream task: analysts rebuild definitions that already exist, duplicate tables proliferate, and nobody can say with confidence where a number came from. Metadata programs are a core pillar of data governance, and increasingly feed master data management and automated lineage tools. The common failure is treating a one-time documentation push as sufficient; metadata that isn't updated as pipelines change goes stale and becomes actively misleading rather than simply absent.
Last reviewed September 22, 2026