A Data Quality Standard (or Data Standard) is a term used to describe a documented agreement on the representation, format, and definition for common data.
Data Quality Standards can be enforced through data quality software. A standard can first be discovered (through data profiling and data discovery) and then continually assessed across the organisation for any breaches that require remediation or an update to the agreed rule for a data quality standard.
Data Quality Standards form part of a mature approach to data quality management because they ensure a unified approach to data entry, thus ensuring greater validity of data at the source of the data lifecycle. Ensuring accurate data from the beginning helps:
To execute a Data Quality Standard operationally typically requires a series of data quality rules to be created. These are often executed via native applications or data quality software. The benefit of using data quality software is that more sophisticated rules can be created and shared more readily across the organisation.
Learn how Data Quality Standards can be managed across the organisation using our modern data quality tool – Aperture Data Studio.