Is Consistency the Same as Quality in Data Reconciliation?
Data quality is often defined as “fitness for use of data.” In one way this strikes the average reader as a kind of vague definition. On the other hand, more seasoned data quality professionals know from experience that the given column in a given table may matter marginally for one use case, but may be very important for a second use case. Thus poor data quality can be tolerated for the first use case, but not for the second. This seems to confirm the idea behind the generalization of data quality as “fitness for use.” But can we do better?