Praveen Murugesan explains how Uber leverages Hadoop and Spark as the cornerstones of its data infrastructure. Praveen details the current data architecture at Uber and outlines some of the unique challenges with data processing Uber faced as well as its approach to solving some key issues in order to continue to power Uber's real-time marketplace.

The next evolution in the on-demand economy is in predictive analytics fueled by live streams of datain effect knowing what customers want before they do. Eric Frenkiel explains how a real-time trinity of technologiesKafka, Spark, and MemSQLis enabling Uber and others to power their own revolutions with predictive apps and analytics.

Schema plays a key role in the Hadoop architecture at Uber. Kelvin Chu and Evan Richards explain why schema is important and how it can make your Hadoop and Spark application more reliable and efficient.