When it comes to data quality best practices, it’s often argued, and sometimes quite vehemently, that proactive defect prevention is far superior to reactive data cleansing. Advocates of defect prevention sometimes admit that data cleansing is a necessary evil. However, at least in my experience, most of the time they conveniently, and ironically, cleanse (i.e., drop) the word necessary.
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