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Every year for the past six years, a consortium of software companies has collaborated to conduct a survey on attitudes and adoption of open-source software in business. The 2013 Future of Open Source survey is now open and taking responses until March 28. Open source analyst group 451 Research is a collaborator again this year, along with Revolution Analytics, Red Hat, Hortonworks, and several other open-source software firms.

M. Edward Borasky has curated a list of resources for budding data journalists looking to use R. Many of the links relate to data scraping, data mashups and data visualization, and so would be useful for data science applications generally. Check it out. (via Hadley Wickham)

Tired of manually running a python script to scrape the latest bookmaker odds on the next Pope, R user AJ (an analytical research manager at a large healthcare company) instead created an R script to track the odds on the Papal successor, and automated it with the Shiny package for R.

Between the Strata conference and various announcements, last week was certainly a busy one for the crew here at Revolution Analytics. So I thought I'd take the opportunity to catch you up on some of the recent media articles you might have missed:

This video below is what the word "inspirational" was made for. My parents gave me my first computer at around age 11 or 12 (a Dick Smith VZ-200), and it literally changed my life. The first "real" program I remember writing was a 2-player version of the Snakes game, written in Basic.

As a gamer, I was especially interested to see what Electronic Art's Rajat Taneja had to say about big data challenges in video games. Here are some of the key stats from his talk at Strata Santa Clatra 2013:

The final installment of the R 2.x series is now available: R 2.15.3 was released this morning. If you build R yourself, the source files can be downloaded from CRAN now; pre-built binaries for Windows, Mac and Linux will be available from the various CRAN mirrors over the next few days. This update mainly fixes a few minor bugs, and is a drop-in replacement for R 2.15.2.

At Tuesday's Data Driven Business Day at the Strata conference I gave my talk, Real-time Big Data Predictive Analytics: From Deployment to Production. My goal in the talk was to explain the buzz-phrases "real time", "big data" and "predictive examples" in the context of a specific example: why are some web ads today uncannily targeted at our personal interests or needs? 

Today, there are two main ways to use Hadoop with R and big data:

1. Use the open-source rmr package to write map-reduce tasks in R (running within the Hadoop cluster - great for data distillation!)