How to apply big data analytics and machine learning to real time processing by Kai Wähner

Why watch

This talk explains how to integrate insights from historical Big Data analysis into real-time transactions using stream processing. It covers frameworks like Apache Storm, Spark, and Flink for processing data in motion, along with machine learning model integration from R and Spark MLlib. The presentation includes real-world success stories and a live demo, targeted at developers and architects building real-time data processing systems.