The Four Stages of Data Quality: From Hidden Costs to Measurable Value
This is the fundamental problem with data quality. You know it matters. Everyone knows it matters. But until you can quantify the impact, connect it to business outcomes, and build a credible business case, it remains this abstract thing that’s important but never urgent enough to properly fund.
I wrote a practical guide to data quality last week that walks through hands-on implementation—the SQL queries, the profiling techniques, the actual mechanics of finding and fixing data issues. Think of that as the “how to use the tools” guide. This article is different. This is the “why these tools matter and how to convince your organization to actually use them” guide.
