If you search on Google for “data quality” you will find the ever-recurring discussion on how we can define data quality.
This is also true for the top ranked none sponsored articles as the Wikipedia page on data quality and an article from Profisee called Data Quality – What, Why, How, 10 Best Practices & More!
The two predominant definitions are that data is of high quality if the data:
- Is fit for the intended purpose of use.
- Correctly represent the real-world construct that the data describes.
Personally, I think it is a balance.
In theory I am on the right side. This is probably because I most often work with master data, where the same data have multiple purposes.
However, as a consultant helping organizations with getting the funding in place and getting the data quality improvement done within time and budget I do end up on the other side.
What about you? Where do you stand in this question?