What is a Data Catalog and what problems does it solve?

Data Catalog

A data catalog is a centralized system for managing metadata about enterprise data assets, enabling users to discover, understand, and trust their data.

Core Problems It Solves

Data silos: Data is scattered across departments, making it hard to know what data exists where.

Poor data understanding: Ambiguous column names like "status" or "type" — no one knows what they mean.

Redundant work: Different teams build the same datasets or metrics independently, wasting effort and creating inconsistent definitions.

Compliance risk: No way to track which tables contain personal or sensitive data (PII).

Key Features

Feature	Description
Data discovery	Search and find needed datasets or columns
Business glossary	Unified definitions for business terms, eliminating ambiguity
Data lineage	Visualize data flow and dependencies
Data quality scores	Display quality assessment results for each dataset
Sensitive data tagging	Mark locations of PII, financial, and other sensitive data

Common Tools

• Open source: Apache Atlas, Amundsen, DataHub
• Cloud-native: AWS Glue Data Catalog, Google Dataplex
• Commercial: Alation, Collibra