A few months ago, I wrote a column asking if the dimensions of data quality, such as accuracy, consistency and timeliness, are real. I pointed out that there are no generally accepted definitions for the dimensions, no generally accepted exhaustive list of them and no generally accepted methodologies for measuring each one.

Since the column was published, I have been "encouraged" to say something a little more positive on this topic – something that will help practitioners deal with the daunting problems of data quality. I agree that being negative is not that helpful, although it is refreshing to have a frank conversation about what really underlies terms that are often thrown about our industry.

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