SAS: 5 Common data quality project mistakes (and how to resolve them)
Over the course of the last eight years, I’ve interviewed countless data quality leaders and learned so much about the common mistakes and failures they’ve witnessed in past projects.
In this post I wanted to highlight five of the common issues and give some practical ideas for resolving them:
\#1: Not connecting data priorities to business priorities
One of the biggest data quality frustrations I’ve witnessed in the business community is a lack of focus on tangible business issues. Data
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