Information Age recently published a feature article devoted to the R language, "Putting the R in analytics". Says author Pete Swabey: Already popular in universities, there are signs that R is finding increasing adoption in the enterprise. This promises to lower the barriers of entry for advanced analytics, and may ... [Read more...]

Multiple Sclerosis (MS) is a debilitating and complex disease with an unknown cause — and for which there is currently no cure. The SUNY Buffalo is home to one of the leading multiple sclerosis (MS) research centers in the world, and as reported in Healthcare IT News, the research team is ... [Read more...]

By Joseph Rickert Revolution’s resident economist, Saar Golde, is very fond of saying that “90% of what you might from a recommendation engine can be achieved with simple techniques”. To illustrate this point (without doing a lot of work), we downloaded the million row movie dataset from www.grouplens.org ... [Read more...]

In the 2012 edition of the SAP Sybase Capital Markets Guide, Revolution Analytics' Senior Advisor for Products and Strategy (and former CEO) Norman Nie writes about the "Five Benefits of Big Analytics". (You can also read his article at Enterprise Innovation.) Norman makes the argument that while sampling and aggregation are ... [Read more...]

The O'Reilly Radar blog has a lengthy and very interesting interview with the lead and deputy CIOs of the Consumer Financial Protection Bureau, the new US government agency devoted to consumer protections in the financial markets. In that interview, they talk about the many open-source tools used in the agency (... [Read more...]

The competition amongst database vendors to create the fastest, most powerful "data layer" — the hardware and software to provide storage for Big Data with high-performance data processing — is clearly heating up. The Netezza appliance has been so successful that IBM has been racing to keep up with demand. SAP is ... [Read more...]

Tomorrow (at 2PM Eastern on Thursday), the White House White House Office of Science and Technology Policy will host a 90-minute forum on Challenges and Opportunities in Big Data. You can watch the event live at the previous link, and see federal government science heads from OSTP, NSF, NIH, DoE, ... [Read more...]

We can add SAP to the list of vendors offering R integration with their products. InformationWeek reports that the new SAP BusinessObjects Predictive Analysis model provides a graphical user interface to R. Created in reaction to "competitive and market forces, including the momentum of open source R", the new module ... [Read more...]

At the recent Big Data Workshop held by the Boston Predictive Analytics group, airline analyst and R user Jeffrey Breen gave a step-by-step guide to setting up an R and Hadoop infrastructure. Firstly, as a local virtual instance of Hadoop with R, using VMWare and Cloudera's Hadoop Demo VM. (This ... [Read more...]

The IBM Netezza analytics appliances combine high-capacity storage for Big Data with a massively-parallel processing platform for high-performance computing. With the addition of Revolution R Enterprise for IBM Netezza, you can use the power of the R language to build predictive models on Big Data. In the demonstration below, Revolution ... [Read more...]

Revolution Analytics' CEO Dave Rich was interviewed by Wikibon's David Vellante and SiliconAngle's John Furrier at the Strata 2012 conference last week. Given Dave's background at Accenture Analytics, the conversation naturally turned to impact of predictive analytics and R on business services. (See the video after the jump, below.) Bret Latmore ... [Read more...]

As explained in detail by Michele Chambers at the IBM Netezza blog, there are two keys to getting fast performance with statistical analysis on massive data sets with R: Massive parallelization: break the problem down into small pieces, and run them in parallel Bring the R engine to the data (... [Read more...]

The past couple of years have seen a dramatic growth in the use of the R language in the enterprise. R has always been pervasive in academia for research and teaching in statistics and data science, and as new graduates trained in R have migrated to the workplace the demand ... [Read more...]

Revolution Analytics' open-source RHadoop project, which provides integration between R and Hadoop, has been updated with the release of version 1.2 of the "rmr" package. New in this version: support for binary I/O formats, which improves on the text-only interfact by allowing use of faster and more space-efficient data formats ... [Read more...]

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Haydn Shaughnessy at The Forbes blog provides a list of the "Top 20 Influencers in Big Data", and I'm humbled to report that yours truly is listed there at #2. It's an instantaneous ranking based on the social-media tracking tool Traakr, but it's still great to be listed alongside writers for SiliconAngle, ... [Read more...]

Revolution Analytics CEO Norman Nie sat down with Cassimir Medford from Business Agility to talk about the problems business today face with respect to Big Data. The two big problems identified: finding adequately trained personnel and locating the right tools. Norman traces the problem of finding skilled practitioners to work ... [Read more...]

EMC last week published the results of a survey of 462 IT decision makers who self-identified as either a data scientist or business intelligence professional (plus 35 invitees who were attendees at the EMC Data Scientist Summity and/or Kaggle competitors). There's a nice summary of the conclusions at the EMC blog, (... [Read more...]

The open-source RHadoop project to integrate R and Hadoop continues apace, with a new version of the rmr package released this week. Changes in this version improve performance when storing and retrieving R objects from Hadoop with a native serialization process, support for equijoins (a MapReduce-style merge) and some new ... [Read more...]

Responding to the birth rates analysis in the post earlier this week on big-data analysis with Revolution R Enterprise, Luis Apiolaza asks at the Quantum Forests blog, do we really need to deal with big data in R? My basic question is why would I want to deal with all ... [Read more...]