
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: 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: 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: 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.
"We've combined Revolution R Enterprise and Hadoop to build and deploy customized exploratory data analysis and GAM survival models for our marketing performance management and attribution platform," said John Wallace, CEO of UpStream Software. "Given that our data sets are already in the terabytes and are growing rapidly, we depend on Revolution R Enterprise's scalability and fast performance. We saw about a 4x performance improvement on 50 million records. It works brilliantly."
For more information, visit www.revolutionanalytics.com/