Most organisations don’t have a data problem — they have a value problem. In this episode, Roland Brown explains how shifting from pipelines to data products turns raw information into trusted, reusable assets that power AI.

He explores why data without design creates noise, how AI exposes weak foundations, and why the path to explainable AI begins with architecture, not algorithms. From the data-to-value chain to the cultural shift of product thinking, Roland shares how ownership, trust, and accountability transform the way data delivers outcomes.

Discover practical insights on:

• Turning infrastructure into impact
• Designing for consumers, not collectors
• Measuring reuse, not rows
• Building the three layers of AI-ready architecture: trust, context, and intelligence

“AI doesn’t run on data — it runs on understanding.”

🎧 Listen to The Data Journey wherever you get your podcasts or visit thedatajourney.com.