When faced with a number of data quality issues, and urgent stakeholder requests to improve quality, it can be tempting to dive right in and clean the data. This however doesn't get to the root of the problem and one finds that many of the same types of problems have to be resolved over and over again. This can be not only ineffective, but also demoralizing when staff have to spend so much time to get back to where they started.
"For the data industry, standardized definitions of data quality dimensions are needed, just as other professions, such as accounting have agreed-upon concepts and terms like “chart of accounts”." --Danette McGilvray, Granite Falls Consulting
