The most commonly asked question about data quality projects is “When will we be finished?”

If we accept that Data Quality degrades over time (some measures for customer data say by as much as 25% per annnum) then the answer has to be “Never!”.

The simple reality is that the moment data quality issues are no longer being addressed data begins to deteriorate due to business process issues, data capture errors or just due to time – for example a client changes jobs and you still have her old work number and email address.

A holistic approach to data quality should include:

1.) Tactical data quality “projects” intended to do root cause analysis and address the source of poor data as well as to scrub current data to address specific issues

2.) Automated application of business logic to maintain new data in the required state.

3.) Ongoing monitoring of data quality against agreed metrics.

The ongoing nature of any the data quality solution requires that it become a consistent and repeatable part of the business as usual (BAU) process. Data Quality can never be maintained via a once off project and this expectation must be managed with both business and IT stakeholders