Data Quality Improvement & Testing (DQI) ensures that the complete solution is ‘fit for purpose’ i.e. it is of a quality appropriate to the needs of the business. This combines both data quality and application quality. It is critical that data is accurate and reliable, and therefore trustworthy. It also recognises that it is not a one off process, but an ongoing programme of activity. By first defining the appropriate data quality criteria the quality of the data is measured (quantitatively and qualitatively), analysed and subsequently improved.

Combining the human and technical factors in the right way will improve data accuracy, and tune the organisation and processes to ensure that the quality of the data is maintained.Application quality focuses on ensuring that, for example, the complete BI environment functions and performs in-line with the expectations and requirements of the end-users.