Catalogs help data teams understand what data they have, who owns it, and how it’s being used.
Make your data discoverable and trustworthy with metadata, lineage, and governance.
Without a catalog, data teams waste time answering basic questions. These tools help centralize metadata, track lineage, and document tables at scale.**Top Catalogs:**- **Castor** — UX-friendly catalog with Slack/BI integrations- **Collibra** — Enterprise-ready governance and policy enforcement- **Atlan** — Open APIs and strong dbt + BI integrationsKey features:- Column-level lineage- Data owners and usage metrics- Searchable documentation
A data catalog is a centralized platform that helps teams document datasets, track metadata, and understand data lineage across systems. It improves discoverability, ensures governance, and saves time by reducing repeated questions about what data exists and how it’s used.
Top catalogs offer column-level lineage, searchable documentation, ownership tagging, and integrations with tools like dbt, BI platforms, and Slack. These features help teams manage data at scale, reduce duplication, and maintain clarity around who owns what.
Data engineers, analysts, and governance teams rely on catalogs to reduce tribal knowledge, enforce data policies, and streamline onboarding. If your team spends too much time asking where data lives or what it means, it’s time to implement one.
While Galaxy isn’t a data catalog, it complements one by helping teams interact with documented data more effectively. With schema-aware autocomplete, AI-powered explanations, and query history, Galaxy acts like a lightweight companion to a catalog — surfacing metadata and improving SQL usability without switching tools.
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