Business analysis glossary
Data Validation
What it is
Data validation is checking that data is complete, correctly formatted, consistent and plausible. It can happen when data is entered, when it moves between systems and when analysts check reports. Checks include format, range, uniqueness, completeness and consistency between related fields or systems.
Why it matters
Decisions are only as good as the data behind them. Validation catches problems such as missing values, duplicates and impossible dates before they reach a dashboard or a customer. Analysts add validation rules to requirements so that bad data is stopped at the door instead of cleaned up later at a much higher cost.
Example
Before reporting on Tidewater Insurance claims, the analyst checks that no claim has a settlement date before its report date, that claim numbers are unique and that every claim links to an existing policy. Each check can be run as a query, and any failing rows are listed for the data owner to correct before the report is published.