Every number on a dashboard is the end of a chain: raw tables are cleaned into staging models, staging models are joined and aggregated into marts, and marts feed the KPI tiles analysts stare at. Data lineage is the record of that chain — which upstream tables and transforms a given number depends on. Good governance means that record is always answerable, so when a number looks wrong you can trace it backward instead of guessing.
Column-level lineage — tracing not just table dependencies but which specific upstream column feeds which output column — is now considered a baseline requirement for regulated industries under frameworks like BCBS 239 and GDPR's data-provenance expectations.
An interactive 3D directed graph of raw tables, staging models, mart joins, and dashboard KPI tiles — click any node to trace its lineage backward through every join and transform to the source table it ultimately depends on.
Backward lineage tracing (a reverse breadth-first walk over dependency edges) is how governance tools answer "where did this number come from?" — collecting every ancestor table, join, and transform a metric depends on.
Pick a dashboard metric or click any node directly. Use trace depth to reveal the backward walk hop by hop, and watch animated particles show which way data actually flows — from raw sources toward the dashboard.
Regulations like BCBS 239 and GDPR increasingly require column-level lineage — not just "this table feeds that table," but exactly which upstream column produced each output field.