Abstract: 

Today, the industry offers numerous systems for the analysis of large amounts of data. Under the hood, they span a variety of interesting and unique architectures. In this talk, we'll discuss why you can never seem to find that single perfect system, and how to think about and evaluate the capabilities of various systems through the prism of a temperature-based spectrum of use cases, from cold to hot analytics.

Bio: 

Zeke Dean is a highly experienced streaming analytics architect with expertise in both Kafka and Apache Druid. He is an expert at wearing multiple hats to satisfy customers in their specific roles and has delivered highly scalable code and distributed systems. He has numerous years of experience building big data systems for enterprises all over the world -- from banks in the Middle East and India to major publishing houses in the United States and a payment platform in Japan. He now works with businesses to solve their analytics requirements on streaming data using the Imply analytics in motion platform based on Apache Druid.