Revolution R Enterprise 6.2: Teradata Connection, Automates Linear Models
New features include a dedicated Teradata connection and new Stepwise Regression for Big Data Linear Models, to speed up time to insight.
PALO ALTO, Calif. April 24, 2013
Revolution Analytics, the leading commercial provider of software, services and support for the open source R project, announced a significant upgrade to its commercial-grade analytics software built upon the world's most powerful open source R statistics language for R-based enterprise-class data analytics. Available now, Revolution R Enterprise 6.2 introduces several new advances in high-performance predictive analytics.
The key new features of Revolution R Enterprise 6.2 include:
- High Speed Teradata Data Connection. Teradata is the first database for which Revolution R Enterprise has a dedicated parallel connection. Customers can seamlessly extract data from a Teradata database using the Teradata Parallel Transporter and write it to a high performance XDF format file, or simply analyze the data directly. The increased speed with which Revolution R Enterprise users can move the data saves a significant amount of time when working with a large dataset.
- Stepwise Regression for 'Big Data' Linear Models. This feature allows users to automate the process of building a model by using a rigorous method to test and select from among a range of variables that are available for use in the model. The result is a dramatic reduction in the total time needed to fit a model.
- Parallel Random Number Generation. This new functionality provides an R interface to the parallel random number generators supplied with the Intel MKL libraries. These provide high quality parallel random numbers for use in distributed computations.
The new release is based on open source R 2.15.3, the latest stable version. Revolution R Enterprise users benefit from 89 new features, 11 performance enhancements and 139 bug fixes from the open source R project.
Revolution R Enterprise 6.2 is available now. For more information, please visit www.revolutionanalytics.com/products/revolution-enterprise.php, or join a webinar at 11AM EST on May 1 introducing the new features.