Data Analytics Monthly Forum

AI is reshaping how you build, test and scale data platforms – you can generate pipelines in seconds, auto-write code and spin up solutions using nothing more than a standard Large Language Model (LLM).

But these outputs aren’t always validated. Code can look right on the surface, however, behave differently with real data, and pipelines that work in isolation don’t always hold up in production. Time saved upfront is often spent later reviewing, debugging and refining.

Join our July Data Analytics Monthly Forum as we explore the opportunities of AI within modern data platforms, the potential risks they pose, and what it means for organisations navigating change in 2026.

You’ll explore what you can build today across Microsoft Fabric, Databricks and LLM tools – from code generation and pipeline design; to test automation and engineering optimisation. Then we will bring it back to delivery: where human expertise is still crucial, where risks start to show up, and what it takes to turn generated outputs into something reliable.

You’ll learn:

• The latest AI-automation capabilities and how they are speeding up common engineering tasks such as testing and documentation.
• Where things start to break down – including unreliable outputs and data-specific issues.
• Why AI-generated solutions often require more validation, debugging and governance than initially expected.
• How to utilise these capabilities whilst ensuring that delivery stays on track without introducing unnecessary risk.

You’ll leave with a clear view of the importance of industry and domain knowledge for AI output validation and learn how to treat AI-automation as an opportunity – not an answer.

Register now!