Definition · data management
Version control of data
Version control of data is the practice of tracking and retaining successive states of a dataset or model so any prior version can be retrieved and compared. For version control of data, the important details are the period, source evidence, reviewer, threshold, and control purpose that make the treatment auditable.
Also known as data versioning, dataset versioning
Why it matters
Understanding version control of data matters because close, reconciliation, and audit work depend on consistent timing, source evidence, review thresholds, and ownership. A loose definition creates avoidable rework. Versioning data means every change produces a new, retrievable state rather than overwriting the last. Pluvo keeps version history and report-run history, so you can restore a prior model and see exactly what changed between runs.
In practice
Close example
Teams use version control of data 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
Versioning data means every change produces a new, retrievable state rather than overwriting the last. Pluvo keeps version history and report-run history, so you can restore a prior model and see exactly what changed between runs.
In practice, teams should define version control of data with a clear source, owner, time period, and decision before they use it in reporting, planning, or operating reviews.
Understanding version control of data matters because close, reconciliation, and audit work depend on consistent timing, source evidence, review thresholds, and ownership. A loose definition creates avoidable rework. Versioning data means every change produces a new, retrievable state rather than overwriting the last. Pluvo keeps version history and report-run history, so you can restore a prior model and see exactly what changed between runs.
A strong workflow for version control of data 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.
Versioning data means every change produces a new, retrievable state rather than overwriting the last. Pluvo keeps version history and report-run history, so you can restore a prior model and see exactly what changed between runs.
FAQ
What is data version control?
Version control of data is the practice of tracking and retaining successive states of a dataset or model so any prior version can be retrieved and compared. For version control of data, the important details are the period, source evidence, reviewer, threshold, and control purpose that make the treatment auditable.
How does versioning data support auditability?
To use version control of data, start with the decision, then confirm the source data, timing, calculation logic, and owner. The analysis is strongest when a reviewer can trace the answer back to the records that produced it.