Data is everywhere, complexity, demands are increasing and enterprise data teams are expected to deliver answers faster than real time. Hence manual data engineering methods can no longer keep up with the demand to build pipelines, deliver trusted data products, power AI/ML workloads, and enforce strict governance. 

In this session, we will explore the evolution of data engineering across it's entire lifecycle:
Day 1 [Build]: How data teams use agentic tooling to discover data, understand requirements, build data models, generate pipelines, and accelerate testing and deployment.
Day 2 [Autonomous Operations]: How intelligent data agents monitor pipelines, investigate failure, pinpoint root causes to keep enterprise data platform / operations running reliably.

Pro tip: This isn't just another trip through the SlidesVerse ;-)