Glossary

What is Data Validation?

Data Validation refers to checks – often automated – that are performed upon data to make sure it meets the entry criteria for the system or repository in which it resides. For example, the value "Two" is not a valid entry in a field which is designed to only accept numeric data. Validity is an important dimension of data quality. However, it is important to remember that, just because data is valid, this does not imply that it is also accurate. For example, when filling in data describing my red jumper, if I erroneously select the colour 'Blue' from the list of available colours, 'Blue' is still a valid entry, but it does not represent the actual colour of my jumper. This is why Data Validation should always be accompanied by Data Quality and Data Governance measures.

26th August 2026

Build trust in your data with 5 practical Data Quality tips to improve accuracy, engage your teams and embed sustainable data quality processes that drive better business decisions.

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