The Anti-Perfectionist Guide to Data Quality

Chapter 1. The Myth of Perfect Data

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“How can we get perfect data?” — this question gets asked daily by data practitioners all over the world, in stand-ups and steering committees and Slack threads nobody reads. It feels like the fundamental question — the north star that justifies the budget. But it’s the wrong question entirely, and the sooner you accept that, the sooner your data quality work will start having a real impact.

My experience has shown me, repeatedly and sometimes painfully, that perfect data is achievable — but not in the way that manuals, software vendor slide decks, or well-known data management frameworks tell you it is. To get perfect data, you need to take an anti-perfectionist approach, which sounds counterintuitive until you’ve lived through the alternative and watched a well-intentioned initiative collapse under the weight of its own ambition. That’s the perfectionist trap, and this book is, more than anything, an escape route from it.

I first learned this lesson while ...