Data Catalog & Lineage

What it is

A data catalog makes datasets discoverable and documented; lineage tracks where a piece of data came from and what downstream depends on it — together, they answer "what is this, and what breaks if I change it."

Key points

• Catalog: searchable metadata (descriptions, owners, schema, sample values) for every dataset — without one, "what data do we even have" becomes tribal knowledge locked in a few people's heads.
• Lineage: traces a field or table back through every transformation to its source, and forward to everything that consumes it — critical for impact analysis before changing a shared table's schema.
• Automated vs. manual lineage: modern tools parse SQL/pipeline code to build lineage automatically; manually maintained lineage documentation reliably goes stale.
• The practical payoff: when a metric looks wrong, lineage is what lets you trace backward to the actual source of the problem instead of guessing.