In the evolving landscape of data and AI, GenAI has emerged as a game-changer for organisations seeking to derive deeper insights from their data. Retrieval-Augmented Generation (RAG) is the ground-breaking technique of combining retrieval-based and generative AI models to seamlessly integrate and enhance data from multiple sources and reducing model hallucinations.

We will explore how RAG leverages GenAI to provide contextually enriched, high quality outputs. With a practical demonstrations, attendees will learn how RAG in Fabric can be implemented to solve complex data challenges. This session will cover the technical underpinnings of RAG, its application in various industries, and the measurable benefits it delivers along with practical guidance on where to get started.

This session is for data professionals, Fabric fans and Data Scientists aiming to harness the latest advancements in GenAI for enhanced data-driven outcomes.