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The latest update to Revolution R Open, RRO 3.2.0, is now available for download from MRAN. In addition to new features, this release tracks the version number of the underlying R engine version (so this is the release following RRO 8.0.3).

Revolution R Open 3.2.0 includes:

Earlier this month TechCrunch published an article of mine, "The Business Economics And Opportunity Of Open-Source Data Science". With this article I wanted to share how open-source software has disrupted the economics of doing business, now that data is a fundamental component of every businesses' operations.

by Andrew Ekstrom
Recovering physicist, applied mathematician and graduate student in applied Stats and systems engineering

We know that R is a great system for performing statistical analysis. The price is quite nice too ;-) . As a graduate student, I need a cheap replacement for Matlab and/or Maple. Well, R can do that too. I’m running a large program that benefits from parallel processing. RRO 8.0.2 with the MKL works exceedingly well.

by Bill Jacobs, Director Technical Sales, Microsoft Advanced Analytics

Today is my 11th wedding anniversary with my wonderful husband Jay, so it's a love-themed Friday post today. Jay and I met before Facebook was a thing, but we've been touched by the congratulations on our timelines today.

R is coming to SQL Server. SQL Server 2016 (which will be in public preview this summer) will include new real-time analytics, automatic data encryption, and the ability to run R within the database itself:

Computerworld's Sharon Machlis published today a very useful list of R packages that every R user should know. The list covers packages for data import, data wrangling, data visualization and package development, but for beginning R users the biggest challenge is usually just dealing with data. To that end, I thought it was worth listing the package for data access and manipulation, which I thoroughly endorse:

by Gregory Vandenbrouck
Software Engineer at Microsoft

This post is the first in a series that covers pulling data from various Windows Azure hosted storage solutions (such as MySQL, or Microsoft SQL Server) to an R client on Windows or Linux.

We’ll start with a relatively simple case of pulling data from SQL Azure to an R client on Windows.

Creating the database

The Azure Management site changes quite often, therefore these instructions are valid “at the time of this writing” :o)