Webinar by Mike Franklin: Emerging Trends in Big Data Software – Spark, MLlib and Beyond

January 25, 2016
Mike Franklin Webinar

Join Mike Franklin, Professor and Director of the AMPLab at UC Berkeley, for a webinar to learn about the future of Big Data software. The AMPLab has reshaped Big Data by developing technologies such as Spark, MLlib and GraphX as components of BDAS, the Berkeley Data Analytics Stack. AMPLab continues to push the envelope in this space for what’s coming next.

In this webinar, you will learn about the following trends:

  1. Integrated stacks vs. silos
  2. Real-time and low-latency predictive analytics
  3. Pipelines for machine learning and advanced analytics
  4. Big data for IoT, high-performance computing and more

View the recorded webinar now:

About Mike Franklin:

Michael J. Franklin is the Thomas M. Siebel Professor of Computer Science and Director of the AMPLab at the University of California, Berkeley. He has over 30 years of experience in the database, data analytics, and data management fields as an academic and industrial researcher, teacher, lab director, faculty member, entrepreneur, and software developer. 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 a 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 a B.S. in Computer and Information Science from the University of Massachusetts in 1983.