Data standard, standard of data... It's easy to get confused. The first term means recording data in line with an agreed structure. The second means recording data with accuracy. Data standards are fundamental to any business use of IT. So is accuracy.
I just read an article that talks about accuracy of data without mentioning data standards. And yet, I think the article is about data standards, not accuracy. William McKnight revisits the Garbage In, Garbage Out (GIGO) meme, correctly noting how this age old saying continues to be vitally relevant. Here's the section where I get confused:
“For example, in a retail situation each store can map their own keyboard. Most won’t, but some will – to take advantage of local trends. A store that sells mostly Combination #3 might change F1 from Combination #1 to Combination #3. It makes life easier at the store, but can create a headache at corporate if it is not prepared to make the adjustment to the data. The store is concerned with getting paid what it is due. Headquarters is concerned with what is selling. In this case, the source doesn’t change, the analytic store will change the data.”
To me, this is a data standards issue. You reassign F1, you go off-standard. You start speaking the wrong language. A data accuracy issue would be if you kept the keys assigned according to the standard, but you hit F1 twice every time you made a sale.
The difference I'm describing is the one between item and value. Data standards ensure, among other things, that the business counts what it's interested in. But data standards can't ensure people count properly. To me, the latter issue is a data quality issue. McKnight
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