Revolution Analytics Defines The Future of R-Statistics

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Revolution Analytics, formerly known as Revolution Computing, announced a new name under new leadership today.  With the new leadership comes a new set of business goals for the statistical analysis software company.  The company announced its official 2010 product roadmap aimed at bringing “professional-class performance, ‘Big Data’ scalability, productivity and ease-of-use to R.”

As a part of the release, Revolution Analytics made two community announcements:

  • The Company’s flagship offering, Revolution R Enterprise, is now being offered free-of-charge to academic users-giving this influential community access to the same full-featured production-grade software available to businesses and large organizations.
  • The beta launch of, a new website for the R community, where R users will be able to find and share resources, ideas and tips.

Today, many R users are highly trained statisticians and data analysts who’ve been instrumental in helping evolve the program,” said Robert Gentleman, co-creator of R and board director of Revolution Analytics. “I believe that by fostering a relationship with the open source and academic communities Revolution Analytics can help drive R’s acceptance in mainstream business.”

So what’s the product roadmap look like?

  • Big Data’ Analysis for Terabyte-Class File Structures: A total solution that combines the use of external memory algorithms, distributed parallel computing, high performance data access and an extensible framework for processing huge datasets in R. A collection of the most common statistical procedures used on big data that are scalable across cores and computers-and are orders of magnitude faster than using legacy tools.
  • Integrated Web Services: A robust programming platform used to deliver R functionality on the Web-one that will support both anonymous R Script execution, and authenticated users working in a stateful environment.
  • Comprehensive Data Analysis GUI: A Web-based user interface that radically improves the usability of R, accelerates productivity and enables rapid learning for both novice and experts. Users will be able to seamlessly transition back and forth between R code and dialogs, and be exposed to only as much R code as they want to see. Built on a fully extensible framework that allows for creating and modifying UI elements (menus, dialogs, outputs), the new GUI lets users customize and extend the UI for their needs.
  • Products and Services to help migrate data and applications from legacy statistical systems to R.

Statistically speaking, if you’re into statistics, you should check out their full product roadmap here.