Data Fitness

In our perpetual fence match to improve Data Quality with arguments, the riposte is often vague and suspected false. The given reasons for parties to counter our initiatives on quality, often are not the real reasons. "Gut feeling" and belief are man's guides when something is difficult to comprehend.

I truly think this is a fact of life and we will have to deal with it. Even if a positive ROI for a DQ initiative can be easily made, we are baffled with amazing counter arguments. I can think of no other explanation than that the term 'Data Quality' has an image issue. And I think it's not the 'Data' part that gives the old-fashioned, scruffy librarian feeling, I think it is the 'Quality' part.

Quality is a neutral word but it has a connotation of difficulty and idealism. If someone speaks of 'Quality', usually the word 'issue' or 'problem' is nearby in the sentence. As with 'Architecture', 'Quality' sounds to the average 'business' person or -executive as something that costs money instead of immediately actively making it.

So stakeholders' arguments that bend the truth a little and turn our proposed efforts down, really are to be expected.

This is why I suggest a new, fresh approach: call it 'Data Fitness'. This has a few pro's:
- It has a positive ring to it, when someone or something is fit, that usually is perceived as a good thing.
- We (Data geeks) like to have data that is 'Fit for purpose', as an indication that is has good quality.
- In communication, when something that is spoken of is 'unfit', then everybody understands something has to be done about it. Our 'gut feeling' tells us this.
A few related concepts I suggest:
- Jog your data, when you are cleansing it, checking 'the tone' when profiling data.
- Incidental jogging does not help. A change of lifestyle is necessary for the data to become and stay fit.
- Not using the term 'cleaner' indicating better data, but 'fitter', that gives a happier feeling.

I could not think of any 'cons'. Or did not want to.

The funny thing is that when you start calling things differently you get another feeling with it. Somehow it feels natural that, when you regularly jog through your databases, data gets attention and gets fitter. If data is left without 'physical' attention, it gets heavy, slow and are sure to lose decision making matches.
People are prepared to put a lot of effort into fitness. Usually of themselves, but I think it will go for the data too. And a lot of work it is, making data fitter.

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