Data validation is the process of verifying that data meets defined quality standards, business rules, and format requirements before it is accepted into a system or used for reporting. Validation checks confirm that data values are within expected ranges, that required fields are populated, that relationships between data elements are logically consistent, and that totals reconcile to expected control figures. Data validation is a technical control that prevents unreliable or incorrect data from propagating through reporting systems.
Why This Matters
Data validation is a preventive control: it stops incorrect or incomplete data from entering reporting systems in the first place, rather than discovering data quality problems after reports have been produced and decisions made on their basis. Well-designed validation rules catch errors at the point of entry — closer to the source where they are easiest to investigate and correct — and prevent the downstream propagation of data quality issues that erode trust in reporting outputs.
Where This Fits
This term sits within the Governance & Data Trust area of Performance & Control.
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