Better Stats, More Data for Revolution R Enterprise

Revolution R unveiled the latest version of its flagship product this week – a commercial distribution of the popular mathematics-oriented programming language optimized use in the enterprise. R Enterprise R 6 introduces a number of new improvements on top of the ones the company has already been touting.

One of the things that they’ve added is visualization at a massive scale: a built in tool named RevoScaleR can process and model terabyte-class data sets at “a fraction of the time of legacy products.” Support for Platform LSF grids is a part of the update as well, and users now running Microsoft are able to offload workloads directly from their on-premise HPC clusters to Azure Burst.

In addition, V6.0 also enhances the functionality of the statistical language itself. R Enterprise is now more tailored to the needs of a number of core verticals, so insurance, finance and biotech firms can use better predicative analytics models. To top it off, users are given access to SAS, SPSS, ASCII and ODBC data without having to pay for additional licenses.

Last but not least, parallel processing speed and overall performance have been increased thanks to the R 2.14.2 Engine. This is supported by the Hadoop connector as well.

“Revolution Analytics continues to drive innovation and revolutionize the predictive analytics industry for the enterprise,” said David Rich, Revolution Analytics CEO. “Already recognized for its speed, data capacity and price performance, we’re very excited about the enhancements to our ‘big data-ready’ R Enterprise solution. Our customers are leaders in their respective markets, and they require high-performance tools to better leverage the explosion of big data, deliver clearer results faster and improve cost-efficiency.”

The fifth version of Enterprise R was only rolled out in November last year.

About Maria Deutscher

Maria Deutscher is a staff writer for SiliconANGLE covering all things enterprise and fresh. Her work takes her from the bowels of the corporate network up to the great free ranges of the open-source ecosystem and back on a daily basis, with the occasional pit stop in the world of end-users. She is especially passionate about cloud computing and data analytics, although she also has a soft spot for stories that diverge from the beaten track to provide a more unique perspective on the complexities of the industry.