AUG 16, 2012 5:15am ET

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Data Quality is Not Fitness for Use

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For as long as I can remember, data quality has been defined as “fitness for use.“

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Comments (8)
Dear Mr. Chisholm, Thanks for a really great article that puts a difficult concept into everyone's understanding! Something that really explains well, the overall premise for data, data quality and the target of correct design. The article, without directly saying so, portrays that all data projects require the upfront business/requirements analysis to better the chances that the correct data is collected. I agree with the inclusion that metadata is key. There are so many projects where the deciders like to skip these pertinent steps as once something is decided, the overall inclination is to 'charge ahead', full throttle, without sufficient exploration / documentation. I'm interested in your interpretation on a question/idea I have ; imagining if I wanted to put the diagram elements (from figure 1) to a data model, to me, Interpretation characteristics would describe to the overall idea of how data should/would be used vs Interpretant characteristics that would probably describe a role, a person ,or, an algorithm of some type. What would your thoughts be on altering on one of the relationships in the diagram to 'Interpretation' from 'Interpretant' having a left-to-right verb association like 'Data is understood as (an) Interpretation' and subsequently, the Interpretation applies Data to 'a' particular use? Whether or not the use is correct would be dependent on the interpretation. Thanks again.
Posted by Robert A | Thursday, August 16 2012 at 1:37PM ET
I concur in offering thanks for an excellent article. Based on my experience, I'd suggest a better title would be "Data Quality is Not Just Fitness for Use". If I may formalize your points (and maybe carry things a bit further), there are three overlapping criteria for data quality: (1) Adequate/Correct representation of the real-world things to be represented. (2) Correct values of attributes compared to real-world. (3) Appropriateness for intended use.

"Fitness of use" is an assessment that cuts across all three criteria, and which gives a framework within which to judge quality.

Let's use your mistake about billing address as an example. If your data model didn't include apartment or other subaddress elements, it would not correctly represent occupancy units within apartment or office complexes (a type 1 problem). If my record had an address number of "502" instead of the correct value of "500", the contents are wrong (a type 2 error). If you intend to mail a brochure to current customers, the data set is clearly relevant, but it you want to place door hangers it is not at all relevant (a type 3 error).

Posted by Mike W | Thursday, August 16 2012 at 2:45PM ET
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