Data catalog: Meaning, types, examples, and tools

A data catalog is a searchable inventory of metadata that helps organizations identify trusted data assets by documenting their location, structure, ownership, lineage, business definitions, and access requirements. It supports analysts, engineers, data stewards, and AI agents by improving data discovery, governance, compliance, and confidence in reporting. Technical catalogs emphasize schemas, column-level lineage, permissions, and open table-format metadata for engineering teams, while business catalogs provide glossary definitions, ownership, certifications, and high-level lineage for analysts and governance teams; organizations often use both together. Examples include AWS Glue Data Catalog, Databricks Unity Catalog, and Apache Polaris for technical use cases, alongside Alation, Collibra, and Atlan for business-focused cataloging. Selecting a tool requires evaluating source coverage, automated lineage, governance controls, AI-enabled search, and usability for nontechnical users. The material also presents Fivetran as a managed integration platform that tracks source schema changes, shares metadata with catalogs, integrates with several catalog systems, and provides governance features intended to keep catalog records current.

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