Join me for a concise yet insightful session about what's next in streaming based on three years of experience working on products with the original creators of Apache Spark, Spark Streaming, and MLFlow at as a Principal TMM engineer. In this purely technical session, data engineers can expect to learn the following:

** What is a data lakehouse on a technical level beyond the hype, why should I care and use it for streaming, and how is streaming data in the lakehouse different?

** Apache Spark and Project Lightspeed: Achieving sub-second latencies in stateless Spark Streaming and predictably low latencies with stateful queries. Learn about the current progress and understand how these advancements directly impact you.

** How many drag-and-drop tools have you seen designed for Spark streaming ETL, and why do they often lead to unmaintainable code? Learn why and how the original creator of Spark Streaming developed an SQL-based, serverless, declarative abstraction layer, drawing on a decade of his experience in Spark Streaming technology. This session will provide a comprehensive technical overview and an in-depth hands-on demo of Delta Live Tables and it's SQL-based Kafka ingestion, drawing from a decade of expertise in Spark Streaming technology.