All or Nothing?

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By David Loshin

One of the most frequently referenced dimensions of data quality is completeness. At a formal level, completeness implies rules specifying mandatory assignment of values to particular data elements. In layman’s terms, that specifies rules to make sure critical attributes are populated with values.

Now there are a few things to think about here regarding the critical nature of
completeness rules for data validity, from the data creation side and from the
data consumption side.… Read More