Data quality should be everyone’s job. And it is in the business intelligence department. It is not a glamorous dress up, smile and relax profession. It is a sweaty, bloody and teary frustrating grind. Some days, it is stimulating and fun!
50% of working hrs — BI resources are in hidden data factories. Hunting for data, finding and correcting errors, and searching for confirmatory sources for data they don’t trust.
60% of working hrs — Data scientists spend cleaning and organizing data.
75% — Total cost associated with hidden data factories in simple operations, where resources are (1) Verifying/validating data quality or (2) Resolving data quality issues.
There are those who have successfully tried the Friday Afternoon Measurement – Spending Friday afternoons measuring the data quality for the previous week. This also helps to qualify and quantify the activities that will be needed to improve data quality the following week.
The One in Ten Rule is also a good method/tool to measure data quality.
You cannot change that which you do not know or understand.