As organizations accumulate thousands of tables, dashboards, and pipelines, two problems appear: people can't find the data they need or know whether to trust it, and nobody can fully answer who can access what or where a number came from. Data catalog and governance tools address both - they inventory data assets, describe them, track lineage (how data flows and transforms), enforce quality, and govern access.
The category spans a few related jobs. Catalogs (Alation, Collibra, Atlan, DataHub, Amundsen, OpenMetadata, Apache Atlas, and the cloud-native Glue/Purview/Dataplex) make data discoverable and documented, with search, business glossaries, and ownership. Lineage tools (OpenLineage, Marquez, Spline) record how datasets derive from each other, so you can trace an error to its source or assess the blast radius of a change. Data quality tools (Great Expectations, Apache Griffin, Databand) test data against expectations and catch problems before they reach reports.
The through-line is trust: a number on a dashboard is only useful if people know what it means, where it came from, that it's fresh and correct, and who's allowed to see it. The pages here cover the open-source projects, enterprise platforms, and cloud-native services across catalog, lineage, and quality.