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100% R and More: Plus What's New in Revolution R Enterprise 6.0

R users already know why the R language is the lingua franca of statisticians today: because it's the most powerful statistical language in the world. Revolution Analytics builds on the power of open source R, and adds performance, productivity and integration features to create Revolution R Enterprise. In this webinar, author and blogger David Smith will introduce the additional capabilities of Revolution R Enterprise, including:

• Multi-processor speed improvements and parallel processing
  
• Productivity and debugging with an integrated development environment (IDE) for the R language
  
• "Big data" statistics, with out-of-memory storage of multi-gigabyte data sets
  
• Web Services for R, to integrate R computations and graphics into Web-based applications
  
• Technical support and consulting services for R

This webinar will be of value to current R users in industry and government who want to learn more about the additional capabilities of Revolution R Enterprise to enhance the productivity, ease of use, and enterprise readiness of open source R. R users in academia will also find this webinar valuable: we will explain how all members of the academic community can obtain Revolution R Enterprise free of charge.

VP of Product Development, Dr. Sue Ranney will also provide an overview of the features introduced in Revolution R Enterprise 6.0 including:

1. Big Data Generalized Linear Model, the new RevoScaleR function that provides a fast, scalable, distributable implementation of generalized linear models, offering impressive speed-ups relative to glm on in-memory data frames
2. Platform LSF Cluster Support, which allows you to create a distributed compute context for the Platform LSF workload manager
3. Azure Burst support added to RxHpcServer
4. Updated R engine (R 2.14.2)
5. Ability to use RevoScaleR analysis functions with non-xdf data sources such as SAS, SPSS or text
6. New methods for RxXdfData data sources including head, tail, names, dim, colnames, length, str, and formula
7. New function rxRoc for generating ROC curves

 

About the Speakers

David Smith has a long history with the R and statistics communities. After graduating with a degree in Statistics from the University of Adelaide, South Australia, he spent four years researching statistical methodology at Lancaster University in the United Kingdom, where he also developed a number of packages for the S-PLUS statistical modeling environment. He continued his association with S-PLUS at Insightful (now TIBCO Spotfire) overseeing the product management of S-PLUS and other statistical and data mining products. David smith is the co-author (with Bill Venables) of the popular tutorial manual, An Introduction to R, and one of the originating developers of the ESS: Emacs Speaks Statistics project. Today, David leads marketing for REvolution R, supports R communities worldwide, and is responsible for the Revolutions blog. Prior to joining Revolution Analytics, David served as vice president of product management at Zynchros, Inc.

Sue Ranney oversees Revolution Analytics' product planning and execution throughout the product lifecycle. She was co-founder of ExaMetrix, the producer of the ExaStat open source environment for analyzing huge data sets. Ranney also served as vice president of development for the data analysis products division at MathSoft (now TIBCO Software), where she co-managed S-Plus releases, and was the co-founder of TriMetrix —the creators of the Axum technical graphics and data analysis package. She holds a Ph.D. from the University of Wisconsin.

 

 

 

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