Rethinking Data Quality in the Age of AI

For decades, organizations have invested heavily in data quality focusing on accuracy, completeness, consistency, and timelines. These things matter significantly, and the effort has been worthwhile. But despite real progress, many organizations still find themselves struggling when it comes to analytics, modernization, and now AI.