Beyond the Prompt: Why Data Modelling Still Matters in the Age of AI

AI can generate code, design data pipelines, create tests, and even propose entire data models in seconds. But generating a technically correct solution is not the same as building the right solution.

Behind every useful data product lies an understanding of business concepts, processes, relationships, and – most importantly -, the questions the data is expected to answer.

In this session, we will explore why data modelling and business understanding become more important, not less, as AI takes over more of the implementation work.

We will look at the role of data engineers and designers in providing the context, semantics, and structure that AI cannot simply infer from a prompt.

Because in the age of “AI-generated everything”, the real competitive advantage may no longer be knowing how to build, but knowing what should be built, and why.