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 Data Governance & AI Readiness area of Performance & Control.