Presented By O'Reilly and Cloudera
Make Data Work
March 13–14, 2017: Training
March 14–16, 2017: Tutorials & Conference
San Jose, CA
Ryan Hafen

Ryan Hafen
Consultant, Hafen Consulting

Ryan Hafen is an independent statistical consultant and an adjunct assistant professor in the Statistics Department at Purdue University. Ryan’s research focuses on methodology, tools, and applications in exploratory analysis, statistical model building, and machine learning on large, complex datasets. He is the developer of the datadr and Trelliscope components of the Tessera project (now DeltaRho) as well as the rbokeh visualization package. Ryan’s applied work on analyzing large, complex data has spanned many domains, including power systems engineering, nuclear forensics, high-energy physics, biology, and cybersecurity. Ryan holds a BS in statistics from Utah State University, an MStat in mathematics from the University of Utah, and a PhD in statistics from Purdue University.


9:00am12:30pm Tuesday, March 14, 2017
Secondary topics:  R
Stephen Elston (Quantia Analytics, LLC), Ryan Hafen (Hafen Consulting)
Average rating: ****.
(4.12, 8 ratings)
Divide and recombine techniques provide scalable methods for exploration and visualization of otherwise intractable datasets. Stephen Elston and Ryan Hafen lead a series of hands-on exercises to help you develop skills in exploration and visualization of large, complex datasets using R, Hadoop, and Spark. Read more.