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by Yaniv Mor, Co-founder & CEO of Xplenty

How do you get Big Data ready for R? Gigabytes or terabytes of raw data may need to be combined, cleaned, and aggregated before they can be analyzed. Processing such large amounts of data used to require installing Hadoop on a cluster of servers, not to mention coding MapReduce jobs in Pig or Java. Those days are over.

InsideBigData has published a new Guide to Machine Learning, in collaboration with Revolution Analytics.

The most entertaining book I've read in the past few months is The Martian, by Andy Weir. It tells the story of astronaut Mark Watney, a member of a six-person mission to Mars in the near future. After an accident early in the mission, Watney is stranded alone on the surface of Mars. The book is the story of his quest for survival.

IEEE — the world's largest professional association for the language of technology — recently published its ranking of the popularity of programming languages. The R language comes in at number 9 in the list.

As announced by Peter Dalgaard for the R Core Team today, R 3.1.1 has been released. Codenamed "Sock it to Me", this is a patch release for R 3.1, and mostly includes minor bug fixes. It also includes some small improvements, including easier access to package help files, improved accuracy when importing data with very large integers, and some clearer warnings and error messages.

In case you missed them, here are some articles from June of particular interest to R users:  

The useR! 2014 conference in Los Angeles opened with 16 tutorials

DataInformed published an article by David Smith on how various companies use R.

With the growing popularity of R, there is an associated increase in the popularity of online forums to ask questions. One of the most popular sites is StackOverflow, where more than 60 thousand questions have been asked and tagged to be related to R.

UseR! 2014, the R user conference held last week in LA, was the most successful yet. Around 700 R users from around the world converged on the UCLA campus to share their experiences with the R language and to socialize with other data scientists, statisticians and others using R.