How Data Quality Failures Drain Billions from Enterprise Revenue

Poor data quality costs enterprises an average of $12.9 million annually and results in 15-25% revenue losses—a growing crisis prompting organizations to adopt automated detection and governance solutions. With over 667 dedicated data quality platforms now available and tools like Great Expectations leading the market, managing data integrity across complex systems has shifted from a nice-to-have to a critical operational imperative. Understanding the true business impact of data quality failures is essential for enterprises seeking to protect revenue and maintain competitive advantage in an increasingly data-driven landscape.