About the Presentation

Poor quality data often leads to major risks in all parts of an organization, affecting operational efficiency, bottom-line results, customer satisfaction and strategic decision making. 

Monitoring, measuring, and quantifying how information quality impacts business objectives on an enterprise wide scale – both financially and non-financially, can become, however, a tricky task.

Based on best practices from several industries and key insights from his book, “Total Information Risk Management: Maximizing the Value of Data and Information Assets,” Dr. Borek shows step-by-step how a data quality risk management program can be set up successfully and how data quality risks can be systematically identified and mitigated. As a result, a value tag can be put on data quality, which allows higher executive buy-in to data quality initiatives to reduce related risks.