In my experience, all organizations cycle through five stages while coming to terms with the daunting challenges of data quality, which are somewhat similar to The Five Stages of Grief. So, in this short video, I explain The Five Stages of Data Quality:
- Denial — Our organization is well-managed and highly profitable. We consistently meet, or exceed, our business goals. We obviously understand the importance of high-quality data. Data quality issues can’t possibly be happening to us.
- Anger — We’re now in the midst of a financial reporting scandal, and facing considerable fines in the wake of a regulatory compliance failure. How can this be happening to us? Why do we have data quality issues? Who is to blame for this?
- Bargaining — Okay, we may have just overreacted a little bit. We’ll purchase a data quality tool, approve a data cleansing project, implement defect prevention, and initiate data governance. That will fix all of our data quality issues — right?
- Depression — Why, oh why, do we keep having data quality issues? Why does this keep happening to us? Maybe we should just give up, accept our doomed fate, and not bother doing anything at all about data quality and data governance.
- Acceptance — We can’t fight the truth anymore. We accept that we have to do the hard daily work of continuously improving our data quality and continuously implementing our data governance principles, policies, and procedures.
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Posts related to the Denial Stage of Data Quality:
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