The definition of data quality as being ”fitness for use” is challenged. “Real world alignment” or similar expressions are gaining traction.
Back in May Malcolm Chisholm made a tweet about the shortcomings of the “fitness for use” definition reported here on the blog in the post The Problem with Multiple Purposes of Use.
When working with data quality in the domain with far the most data quality issues being the quality of contact data (customer, supplier, employee and other party master data) I have many times experienced that making data fit for more than a single purpose of use almost always is about better real world alignment. Having data that actually represents what it purports to represent always helps with making data fit for use, even with more than one purpose of use.
In practice that in the contact data realm for example means:
- Getting a standardized address at contact data entry makes it possible for you to easily link to sources with geo codes, property information and other location data for multiple purposes.
- Obtaining a company registration number or other legal entity identifier (LEI) at data entry makes it possible to enrich with a wealth of available data held in public and commercial sources making data fit for many use cases.
- Having a person’s name spelled according to available sources for the country in question helps a lot with typical data quality issues as uniqueness and consistency.
Also, making data real world aligned from the start is a big help when maintaining data as the real world will change over time.
Data quality tools will in my eyes also have to apply to this trend as discussed with Gartner in the post Quality of Data behind the Data Quality Magic Quadrant.