09 April 2013

R version 3 released

Big Data and Big Analytics open an entirely new opportunity for data-driven organizations.  Data sets that were previously unmanageable are now opening up worlds of possibility due to flexible and powerful platforms to manage the scale and complexity associated with crunching massive data. Now with the capacity, reliability and productivity enhancements of Revolution R Enterprise for PureData System for Analytics, organizations will be able to perform a wide-range of functions that others simply cannot.  Advanced R computations are available for rapid analysis of hundreds of terabyte-class data volumes – and can deliver 10-100x performance improvements at a fraction of the cost compared to traditional analytics vendors.

Download the Revolution R Enterprise for IBM PureData System for Analytics Datasheet:

Download a 90-Day Evaluation copy of Revolution R Enterprise for IBM PureData System


Here’s how these solutions work together:

  • Revolution R Enterprise consolidates all analytics activity into a single appliance.  Many algorithms have been optimized to run in parallel on the PureData System for Analytics.
  • Revolution R Enterprise brings high-performance, enterprise-readiness and support to R along with the ability to integrate advanced analytics into BI front-ends or Microsoft® Excel™. These extensions to the already-powerful R allow Revolution R Enterprise to have a significant impact across all functions in an organization.
  • PureData System for Analytics architecturally integrate database, server and storage into a single, purpose-built, easy-to-manage system that minimizes data movement, thereby accelerating the processing of analytical data, analytics modeling and data scoring. It delivers exceptional performance on large-scale data, while leveraging the latest innovations in analytics.

R version 3 released

The R language marks a major milestone today with the release of R 3.0.0 (codename: "Masked Marvel"). The increment in the version number reflects not a fundamental change in the R langauge itself, but a recognition that the R codebase has matured to a point where closing out the 2.x series makes sense. 
Nonetheless, this release does include some major behind the scenes updates, not least of which is the introduction of big vectors to R, which eliminates some big data restrictions in the core R engine by allowing R to better use the memory available on 64-bit systems. Tal Galili lists the new functionality available in R 3.0.0 and provides a guide to upgrading and re-installing packages.
From everyone here at Revolution Analytics, our thanks go to the members of the R Core development team, who have volunteered so much time and expertise to furthering the R Project. The world of statistical computing would be a much poorer place without their contributions.
If you build R yourself, R version 3.0.0 is available for download in source from CRAN, and pre-built binaries (for Windows, Mac and Linux) will be available in the next couple of days. For Revolution R Enterprise users, the next release (version 6.2) will be based on the recently-released final Rv2 engine (R 2.15.3). We're currently working on integration of Rv3 for inclusion in a major update to Revolution R Enterprise in late 2013.
R-announce mailing list: R 3.0.0 is released

Here below you find a replay of the Webinar on Revolution Analytics:
Analyzing Big Data on Netezza and Pure Analytics with Revolution-Analytics
Everyone involved in high-stakes analytics wants power, speed and flexibility regardless of the size of the data set and complexity of the analysis. Trailblazing organizations that have deployed IBM Netezza Analytics with their IBM Netezza data warehouse appliances (TwinFin) with Revolution R Enterprise are getting all three. Register for this webinar to find out how.
To set the stage, we’ll provide a brief overview of the “R” statistical analysis language, the Revolution R Enterprise framework (with R at its core) as well in-database analytics on IBM Netezza Analytics Appliances. We’ll be talking about what Revolution Analytics brings to IBM Netezza, and vice versa.
Then, we’ll complete a model-building exercise from start to finish using the combined Revolution R Enterprise and IBM Netezza solution and demonstrate the performance and flexibility of the integrated offer. Join us as we:
  • Begin with data visualizations and summary statistics to gain an understanding of our data 
  • Split the data into training and test sets for model building
  • Build models and
  • Measure accuracy on both our training and test set and visualize the results.

, and here is the demo:

, if youy are stressed for time, here are the slides:

For more information please contact me at:
Drs. Albert Spijkers
DBA Consulting
web:            http://www.dbaconsulting.nl
blog:            DBA Consulting blog
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email:          info@dbaconsulting.nl 

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