How to Create a Data Catalog
Build a searchable data catalog that documents datasets, schemas, ownership, and lineage across your organization.
What You'll Learn
This intermediate-level guide walks you through how to create a data catalog step by step. Estimated time: 10 min.
Step 1: Inventory your data assets
Discover and document all databases, tables, APIs, files, and data products across your organization.
Step 2: Add metadata and documentation
Enrich each data asset with descriptions, column definitions, data types, business context, and usage examples.
Step 3: Implement data lineage
Track how data flows from source systems through transformations to final analytics tables and reports.
Step 4: Set up search and discovery
Enable full-text and faceted search so analysts can find relevant data assets quickly.
Step 5: Establish governance processes
Define data ownership, stewardship roles, and processes for keeping the catalog accurate and up to date.
Frequently Asked Questions
Which data catalog tool should I use?▾
DataHub for open-source flexibility, Atlan for modern UX, or dbt docs for dbt-centric teams. Choose based on your scale and governance needs.
How do I keep the catalog up to date?▾
Automate metadata extraction from databases and dbt, integrate with CI/CD pipelines, and assign data stewards responsible for documentation accuracy.
Is a data catalog worth the investment?▾
Yes, for organizations with more than 10 data sources. Catalogs reduce time-to-insight by 30-50% by eliminating the data discovery bottleneck for analysts.