Business Intelligence for the Real Time Enterprise

August 31, 2015 - Kohala Coast, Hawaii

Keynote


Real-Time Analytics: The Third Time's a Charm?



Abstract

There's lots of excitement around streaming and real-time in the Big Data world these days. Systems like Spark Streaming, Kafka, Kinesis, Heron, etc. are garnering a lot of press and blog space. As with many other topics in CS, interest in real-time data processing and analytics ebbs and flows periodically, spawning start up companies and predictions of major architectural shifts. To date, however, we have not seen any real breakout product successes. In the database community, there have been at least two previous periods of intense activity in this area. As a veteran of the second wave, who largely has been sitting out this current third one, I'll review some of the past work in the area, and then look at why things could be different this time or why they might not be.


Keynote speaker

Michael J Franklin (UC Berkeley)


Michael J Franklin

Michael J Franklin is the Thomas M. Siebel Professor of Computer Science and Chair of the Computer Science Division in the EECS Department at the University of California, Berkeley. Prof. Franklin is also the Director of the Algorithms, Machines, and People Laboratory (AMPLab) at UC Berkeley, a leading academic Big Data analytics research center. AMPLab has produced industry-changing open source software including Apache Spark and BDAS, the Berkeley Data Analytics Stack. Prof. Franklin is a co-PI and Executive Committee member for the Berkeley Institute of Data Science, a campus-wide initiative to advance Data Science Environments. He was founder and CTO of Truviso, a data analytics company that was subsequently purchased by Cisco Systems. He currently serves on the Technical Advisory Boards of a number of data-driven technology companies, including Databricks, an AMPLab spinout. He is a Fellow of the ACM and a two-time winner of the ACM SIGMOD "Test of Time" award, and received the outstanding Advisor Award from the Computer Science Graduate Student Association at Berkeley. He received the Ph.D. in Computer Science from the University of Wisconsin in 1993, a Master of Software Engineering from the Wang Institute of Graduate Studies in 1986, and the B.S. in Computer and Information Science from the University of Massachusetts in 1983.