AI projects need good data management to be successful, but it often becomes an afterthought for a lot of teams—but it shouldn't. In this episode, Arun Krishnakumar joins Chris Youngblood to discuss why successful AI projects begin with meticulous data management. From collection and storage to transformation and analytics, Arun breaks down the essential components of a robust data platform and explains how good data management directly impacts AI performance.
You'll learn common pitfalls to avoid, how AI itself can improve each step of the data lifecycle, and why security and interoperability aren't just compliance checkboxes but critical parts of your AI strategy. Arun also shares real-world examples from enterprise environments, illustrating how thoughtful data practices lead to smarter insights.
Whether you're starting your first AI project or optimizing an existing data pipeline, this conversation will help you build a stronger foundation—and better results.
