You are here

Revolution Analytics Brings Big Data Decision Trees and New Hadoop Support to Predictive Analytics


PALO ALTO, Calif.

Revolution Analytics, the leading commercial provider of software, services and support for the open source R project, today unveiled the latest version of Revolution R Enterprise, its commercial-grade analytics software built upon the world's most powerful open source R statistics language for R-based enterprise-class data analytics. Revolution R Enterprise 6.1 introduces several new advances in high-performance predictive analytics. It gives users new ability to create big data decision trees, and easily extract and perform predictive analytics on data that is stored in the Hadoop Distributed File System (HDFS).

"Revolution Analytics is dedicated to helping organizations and R developers leverage the power of R for real time data analytics," said David Rich, Revolution Analytics CEO. "Our new release delivers several new features to help organizations with complex and fast-growing data sets make sense of big data. With this new version, Revolution Analytics once again sets a new standard for data analytics."

Revolution R Enterprise 6.1 includes the following new capabilities:

  • Big data decision trees. The new "rxDTree" function is a powerful tool for fitting classification and regression trees, which are among the most frequently used algorithms for data analysis and data mining. The implementation provided in Revolution Analytics' RevoScaleR package is parallelized, scalable, distributable and designed with big data in mind. Revolution R Enterprise continues to offer a wide range of other big-data analysis algorithms, including summary statistics, crosstabs, regression, generalized linear models and K-means clustering.
  • New ability to analyze data from Hadoop Distributed File System (HDFS). With more and more data stored in Hadoop, this new option lets data scientists read data from HDFS and apply big-data statistical models from Revolution R Enterprise.
  • Improved performance for 'Big Data' files. RevoScaleR's 'XDF' file format provides fast access to big data. With new compression technology the size of XDF files can be reduced, allowing for higher-performance analytics throughput and faster transfers into clusters or cloud processing systems.
  • Improved Linux installer. The installation process on Linux servers has been streamlined to meet stringent IT requirements, especially for non-root installs.
  • SiteMinder single-sign for applications: Authorized users of applications built on Revolution R Enterprise deployed via the RevoDeployR Web Services API may authenticate using CA SiteMinder(r).

Revolution R Enterprise 6.1 is available now. For more information on the new platform, register for the free webinar, "New Ad vances in High Performance Analytics with R: 'Big Data' Decision Trees and Analysis of Hadoop Data," which will explore new features. The webinar will take place on November 15, 2012.

Additional details on Revolution R Enterprise can be found at http://www.revolutionanalytics.com/products/revolution-enterprise.php.

About Revolution Analytics

Revolution Analytics is the leading commercial provider of software and services based on the open source R project for statistical computing. The company brings high performance, productivity and enterprise readiness to R, the most powerful statistics language in the world. The company's flagship Revolution R Enterprise product is designed to meet the production needs of large organizations in industries such as finance, life sciences, retail, manufacturing and media. Used by over two million analysts in academia and at cutting-edge companies such as Google, Bank of America and Acxiom, R has emerged as the standard of innovation in statistical analysis. Revolution Analytics is committed to fostering the continued growth of the R community through sponsorship of the Inside-R.org community site, funding worldwide R user groups and offering free licenses of Revolution R Enterprise to everyone in academia.

Media Contact
Lesley Sullivan
Schwartz MSL
Phone: (781) 684-6240
Email: revolutionanalytics@schwartzmsl.com