Top companies like LinkedIn, Uber, and Airbnb have built production data pipelines with Apache Kafka. Joseph Adler, Ewen Cheslack, and Ian Wrigley guide participants through building a secure, scalable, reliable, high-speed ETL pipeline that moves data from production systems to analytical and reporting databases.
Joseph Adler has many years of experience in data mining and data analysis at companies including DoubleClick, Verisign, and LinkedIn. Currently, he is director of product management and data science at Confluent. He is the holder of several patents for computer security and cryptography and the author of Baseball Hacks and R in a Nutshell. He graduated from MIT with a BSc and MEng in computer science and electrical engineering.
Ewen Cheslack-Postava is an engineer at Confluent building a stream data platform based on Apache Kafka to help organizations reliably and robustly capture and leverage all their real-time data. Ewen received his PhD from Stanford University, where he developed Sirikata, an open source system for massive virtual environments. His dissertation defined a novel type of spatial query giving significantly improved visual fidelity and described a system for efficiently processing these queries at scale.
Ian Wrigley is a Technical Director at StreamSets, the company behind the industry’s first data operations platform. Over his 25-year career, Ian has taught tens of thousands of students subjects ranging from C programming to Hadoop development and administration.
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