Definition · data governance
Data lineage
Data lineage is the traceable record of where data originates and how it moves and transforms from source systems through to a final number or report. For data lineage, the important details are the period, source evidence, reviewer, threshold, and control purpose that make the treatment auditable.
Also known as data lineage tracking, lineage to source
Why it matters
Understanding data lineage matters because close, reconciliation, and audit work depend on consistent timing, source evidence, review thresholds, and ownership. A loose definition creates avoidable rework. Lineage is native to Pluvo: its bitemporal ontology records every claim's source and timing, so any figure traces back through the definitions and inputs, and the point in time, it was computed from.
In practice
Close example
Teams use data lineage during close, review, or audit support when a balance or transaction needs evidence. The controller should be able to trace the number to source records, timing, reviewer, and control threshold.
Pluvo example
Lineage is native to Pluvo: its bitemporal ontology records every claim's source and timing, so any figure traces back through the definitions and inputs, and the point in time, it was computed from.
In practice, teams should define data lineage with a clear source, owner, time period, and decision before they use it in reporting, planning, or operating reviews.
Understanding data lineage matters because close, reconciliation, and audit work depend on consistent timing, source evidence, review thresholds, and ownership. A loose definition creates avoidable rework. Lineage is native to Pluvo: its bitemporal ontology records every claim's source and timing, so any figure traces back through the definitions and inputs, and the point in time, it was computed from.
A strong workflow for data lineage separates the definition from the action: first agree what the term means, then decide how it is measured, when it changes, and who is accountable for the next step.
Lineage is native to Pluvo: its bitemporal ontology records every claim's source and timing, so any figure traces back through the definitions and inputs, and the point in time, it was computed from.
FAQ
What is data lineage?
Data lineage is the traceable record of where data originates and how it moves and transforms from source systems through to a final number or report. For data lineage, the important details are the period, source evidence, reviewer, threshold, and control purpose that make the treatment auditable.
What is the difference between data lineage and data provenance?
The boundary for data lineage differs from related terms by scope, source data, time period, and decision use. In this glossary, it covers the traceable record of where data originates and how it moves and transforms from source systems through to a final number or report, so teams should compare those boundaries before using it in reporting or planning.
Why does data lineage matter for audit?
Understanding data lineage matters because close, reconciliation, and audit work depend on consistent timing, source evidence, review thresholds, and ownership. A loose definition creates avoidable rework. Lineage is native to Pluvo: its bitemporal ontology records every claim's source and timing, so any figure traces back through the definitions and inputs, and the point in time, it was computed from.