I'm co-authoring a book on data quality. This paper came up multiple times in my research.

**Why it matters to data science:**
Data cleaning is an integral part to data science workflows and data scientists/analysts are often the "consumers" this article is talking about (even if the title didn't exist back then). Learning how to talk about data quality can empower you to make better requests from upstream sources that impact your work.

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I recently had to define data quality for a chapter in the book I'm writing. A big piece of writing this content …

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