While cutting-edge AI applications capture the spotlight, the real transformative work lies beneath the surface: in building a robust, scalable data foundation. To truly leverage AI, companies are investing in a foundational model house that addresses every stage of the data journey. This includes designing comprehensive data architectures, establishing rigorous data governance, and implementing scalable analytics processes. But what are the technical strategies and frameworks needed to build this foundational model house? Learn from the data scientist who played a pivotal role in constructing this framework — covering everything from technical roadmaps and data pipelines to scalable infrastructure — and discover the tangible impact this approach has on delivering AI-driven insights at scale.

You will learn, in this session, about:

• Why advanced analytics and AI/ML starts with data and how this is 80% of the effort
• What the technical challenges and solutions are, in model house development
• How to architecting data pipelines and systems for end-to-end analytics