Data Quality Strategy

The University has a Data Quality Strategy which aims to ensure a consistent approach to data quality across the student record systems. The strategy outlines the principles that underpin good data quality and the University’s approach to those principles

THE DEFINITION OF GOOD DATA QUALITY

Accurate the data should always display an accurate picture of the student’s record.

Reliable the data should be collected via the standard process.

Relevant the data should be regularly reviewed to ensure that it is always relevant to the University’s requirements.

Valid data should be validated before it is submitted for decision making processes.

Timely the data should be made readily available as quickly as possible in order that decisions are based on current data.

THE PRINCIPLES OF DATA QUALITY

Documentation having appropriate documentation available to ensure users are able to follow the correct process.

Training setting a requirement that users receive high quality training and updates on a regular basis.

Input ensuring that the defined business processes are adhered to and amended when necessary.

Verification having a robust mechanism in place to verify data.

Output ensuring that when data is used to report on performance it is used appropriately and consistently.

Awareness ensuring that staff have an understanding of the need for good data quality and how this contributes to the University’s requirements of having data fit for purpose.