Data lineage tracks where data originates, how it moves, and how it’s transformed from source to final destination across the entire data pipeline. It isn’t limited to a single database; it follows data through multiple systems and processes, showing every transformation and movement along the way. This understanding is documented with lineage diagrams that visualize data flow, metadata catalogs that describe data assets and their relationships, and automated lineage tools that capture and maintain the lineage over time. This combination provides a complete picture of data provenance, which is essential for governance, impact analysis, and auditing. For example, if a revenue figure comes from a source file, undergoes several ETL steps, and ends up in a data warehouse, lineage would show the source, each transformation, and the destination. The idea that lineage is documented only in source code comments or that it isn’t useful for governance doesn’t fit how lineage is used in practice.