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Data is inherently messy. Is that really such a bad thing?

August 2, 2018


A data quality expert once told me that vendors providing data quality software solutions should always ensure 100 percent quality data, and if they didn’t, they should be liable for any ensuing issues. I disagreed with that harsh assessment then—and still do. The truth is, sometimes 100 percent data quality isn’t necessary and could even hinder an organization’s ultimate business goals.

As much as you would like our data to be perfect and pristine, to conform to your established dimensions of data quality, it isn’t.

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