Conceptualisation to Consumption: Rethinking Data Products with AI

“What we’re hearing time and time again is executives want to be able to have a natural conversation with their data. They want to accelerate their data governance journey and democratize those data assets to unlock new use cases.“

–Glenda O’Keefe, Field CTO, Quest Software

Here's an uncomfortable truth about data products.

Most organizations have already done the hard work — the warehouses, the governance frameworks, the data models. And yet business users still can't easily find, trust, or use the data they need.

So, what's actually broken?

In this episode of Data Enablers, Sarit speaks with Glenda O'Keefe, Field CTO at Quest Software, about the real gap between data infrastructure and data empowerment, and why bridging the gap looks very different in 2026 than it did five years ago.

You’ll hear

Why the traditional model, build the technology stack first, find the use case later, has repeatedly failed organizations, and what the outcome-first alternative looks like in practice.
Why C-suite leaders are now entering vendor conversations earlier than ever, and what that signals about where data investment decisions are heading.
How AI is breaking down the language barrier between engineers and business users, letting each speak their own language while drawing insight from the same data.
Why one insurance customer was spending 80% of their time finding and cleaning data, and how that ratio was flipped using AI-powered governance.

Episode Insight

Data products are no longer just about infrastructure or pipelines, they must be trusted, curated, and be easily consumable assets that connect business challenges to actionable insights.

As Glenda highlights, AI is reshaping the data ecosystem by enabling self-service data access, reusable data assets, and faster creation of data products. The real transformation happens when organizations bridge the gap between technical data platforms and business decision-makers, allowing everyone to interact with data in their own language.