What is a Data Quality Standard?
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.
Why are Data Quality Standards important?
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:
- Keep you compliant with data regulations (such as the GDPR)
- Builds customer relationships due to better communication and less mistakes.
- Reduces costs through wasted communications
How can you implement Data Quality Standards?
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.