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Revolution Analytics' big data platform built on open source R language

Revolution Analytics debuted today a major upgrade of its R Enterprise platform for handling big data.R Enterprise 6.
Written by Paula Rooney, Contributor

Revolution Analytics debuted today a major upgrade of its R Enterprise platform for handling big data.

R Enterprise 6.0, which like its predecessor is based on the open source R statistics language, is designed to give enterprises better ways of handling big data and discover "hidden correlations" in data to transform businesses, the company said in a statement.

Version 6.0 offers new scalability and performance characteristics necessary for analyzing data on the cloud and within the enterprise. The company boasts Google and Bank of America among its customers.

Here's how the Palo Alto, Calif. company describes the new capabilities of the upgraded platform, whose general availability is scheduled for June 5:

"Using the built-in RevoScaleR package in Revolution R Enterprise, R users can process, visualize and model terabyte-class data sets in a fraction of the time of legacy products –without requiring expensive or specialized hardware.  Key highlights of Revolution R Enterprise 6.0 include:

  • Platform LSF Cluster Support—Now supports distributed computing on multi-node Platform LSF grids. Support on Windows-based grids provided via Microsoft HPC Server.
  • Cloud-based Analytics with Azure Burst—Switch computations from a local Microsoft Windows HPC Server cluster to the Azure Cloud with a single command. To see a demo of this new capability, visit:http://youtu.be/0cPVXV1DA4o?t=1m34s
  • Big-Data Generalized Linear Models—Support big-data predictive models used in insurance, finance and biotech industries. Use a multi-node server or distributed grid for fast analytics on big data. To see a demo of this new capability, visit: http://youtu.be/_m3K84aJdhY?hd=1&t=1m10s
  • Direct Analysis of SAS, SPSS, ASCII and ODBC Data—Analyze proprietary data formats without the need for SAS/SPSS licenses. To see a demo of this new capability, visit: http://youtu.be/Ug8LtSourCg?t=56s
  • Updated R 2.14.2 Engine—Improves performance and parallel programming capabilities. In addition, Revolution Analytics’ open-source RHadoop project (for Hadoop integration) is updated to work with this new engine.

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