The combination of SAS analytics and Cloudera’s enterprise data hub (EDH) is a common recipe for Analytics at Scale. While Cloudera’s EDH makes it not only feasible but economically viable to store and manage extreme volumes of data in one place, SAS’ In-Memory Analytics gives you the power to analyze and mine data at Scale … all on a single system. With SAS’ In-Memory Statistics for Hadoop and supporting products, business users can use their existing SAS skills to analyze and mine vast volumes of data on the EDH.
In this webinar we will cover:
Mike Ames – Sr. Director, Data Science and Advanced Analytics Product Management, SAS
Mike Ames leads SAS’ Data Science and Advanced Analytics technology product management team. Current initiatives of interest include: self-service data management, in-memory analytics, entity analytics and automated anomaly detection for Hadoop. Since joining SAS in 2002, Ames has led the development of a variety of analytic solutions for clients in the financial services industry. His areas of interest include machine learning, distributed computing and complex event processing. Mike holds a BBA in economics and studied computer science at the University of Georgia and earned an MBA from the University of North Carolina Chapel Hill.
Eli Collins - Chief Technologist, Cloudera
Eli is Cloudera's Chief Technologist. He spent the previous four years leading the team responsible for Cloudera's Hadoop distribution (CDH), and is an Apache Hadoop committer and PMC member. Prior to joining Cloudera, Eli worked on processor virtualization and Linux at VMware. Eli holds Bachelor's and Master's degrees in Computer Science from New York University and the University of Wisconsin-Madison, respectively. You can find him on Twitter at @elicollins.