Question 1

What's the difference between a Data Catalog and a Data Dictionary?

Accepted Answer

A data dictionary describes fields and schemas (for example, what a column means and its data type). A data catalog is broader: it helps you find datasets across the organization and typically includes search, ownership, tags, classifications, lineage, usage metrics, and links to documentation and policies. In practice, a data dictionary is often one component inside a data catalog.

Question 2

When should I use a Data Catalog?

Accepted Answer

Use a data catalog when you have many datasets (data lake, warehouse, streaming topics) and people struggle to find the right data, trust it, or understand who owns it. It’s especially useful when you need governance features like classifications (PII), business glossary terms, lineage for impact analysis, and standardized documentation for self-service analytics.

Question 3

How much does a Data Catalog cost?

Accepted Answer

Costs depend on the provider and how you collect metadata. Common pricing factors include: (1) number of assets/metadata objects stored, (2) scanning/harvesting frequency and volume (how much data you crawl to extract schema and classifications), (3) API calls and search queries, and (4) optional governance features (lineage, policy enforcement integrations). Also budget for operational effort: onboarding sources, curating metadata, and maintaining ownership and glossary terms.

Data Catalog

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