TDWI World

Prerequisite: None

Thomas C. Redman

Bad data bedevils all organizations, increasing costs, angering customers, making risk management more difficult, and slowing revenue growth. Companies employ elaborate technologies, processes, and entire groups to find and fix the errors, but results are far from satisfactory. While most bemoan bad data, an intrepid few recognize that cleaning data errors is futile—there is simply too much data and too many errors to keep up. They take a different tack, addressing data quality at the source, uncovering the root causes of error, and eliminating whole categories all at once. This session traces the habits of the program leaders who succeed in dramatically improving the quality of corporate data.