Tom Redman
The Data Doc, President
Data Quality Solutions

By now everyone knows that AI succeeds or fails on the quality of answers/inferences/predictions it returns.  (Poor) data quality  also gets in the way of day-in, day-out work and good decision-making.  The usual response is to try to find the errors and clean them up.  It is time-consuming, expensive, and frustrating.  And plenty of errors leak through.  No wonder people don’t trust data.

Fortunately there is a better way:  Pro-actively finding and eliminating the root causes of all those errors!  Saves time and money.  Builds trust.  And people like the work!

In this workshop we’ll craft the business case for data quality by comparing “clean-up” versus “eliminating root causes.”  The goal is to help participants grow increasingly intolerant of bad data and start addressing the issues pro-actively.

Mark Ramsey
Managing Partner
Ramsey International LLC

In the era of exploding demand for Generative AI, organizations face unprecedented challenges and opportunities in modernizing their data strategies. This session will explore how a robust data foundation—encompassing governance, quality, integration, and analytics—is essential to unlock AI’s full potential. Dr. Ramsey will share his insights on the immediate actions Chief Data Officers should take to transform data practices, build scalable and trustworthy data architectures, and leverage AI-driven innovations. Attendees will learn how to stay competitive by aligning their data strategies with the rapid growth of Generative AI, ensuring operational efficiency, new revenue streams, and sustained leadership in a data-driven organization.