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SmartData Collective > Big Data > Data Mining > Intelligent Enterprise on R, SAS and REvolution Computing
Data MiningPredictive Analytics

Intelligent Enterprise on R, SAS and REvolution Computing

DavidMSmith
DavidMSmith
2 Min Read
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Intelligent Enterprise follows the story of SAS’s forthcoming integration with R, including the news that the SAS/IML studio integration is scheduled for release this summer. Seth Grimes, the author, has this to say about R:

Why R? The language is algebraic, relatively easy to learn, and powerful, with many analysis, visualization, and interface packages available for free download. It’s great for prototyping algorithms and for exploratory analysis. R has its limitations, for instance scalability, but robustness and reliability are not among them.

Other than describing scalability as a limitation (true in the past, but addressed now with packages like biglm and ParallelR), the article provides some… 

Intelligent Enterprise follows the story of SAS’s forthcoming integration with R, including the news that the SAS/IML studio integration is scheduled for release this summer. Seth Grimes, the author, has this to say about R:

Why R? The language is algebraic, relatively easy to learn, and powerful, with many analysis, visualization, and interface packages available for free download. It’s great for prototyping algorithms and for exploratory analysis. R has its limitations, for instance scalability, but robustness and reliability are not among them.

Other than describing scalability as a limitation (true in the past, but addressed now with packages like biglm and ParallelR), the article provides some positive coverage for R. There’s also some coverage of other commercial companies working with R, including REvolution Computing’s commercial support and extensions for R.

Seth Grimes: SAS gets with the (open source) program.

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