In case you missed them, here are some articles from November of particular interest to R users.
In the webinar "Real-Time Predictive Analytics with Big Data", I showed how R fits into a real-time production system.
R package developer Yihui Xie shares his favorite software and hardware in an interview with The Setup.
Hadley Wickham created a handy tutorial for the Rcpp package, describing how to combine fast C++ code with R (even if you don't know C++).
R is used in the Human Resources department at Facebook (and is displacing Excel for HR generally).
Applications are open for the 2013 John M Chambers Statistical Software Award.
The 2013 useR! conference will be held in Spain, and abstracts are invited from participants for contributed talks.
A video tour of R, for beginners.
By measure of the number of characters it takes to express common tasks in various languages, R is ranked as the third most concise language.
The Slidify package creates presentations from literate R code, and is a more modern-looking and Web-aware alternative to "beamer".
Benchmarks of the time required for the biglm package to process some big-data GLM analyses.
RStudio releases Shiny, a new package to make interactive web-based applications with R.
John Deere uses R to speed up the production of tractors and to forecast crop yields, as shown in this webinar replay.
Revolution R Enterprise 6.1 is now available, with big-data tree models, a Hadoop HDFS connection, and improved performance.
Another take on of using ggplot2 to visualize the DW-NOMINATE data on ideology shifts in the US Congress.
I present the Data Scientist's Tookit (including R, of course) in this replay of my webinar, The Rise of Data Science in the Age of Big Data Analytics.
An animated map created with R shows US presidential candidates travelling across the USA.
Some non-R stories in the past month included: a time-lapse movie of edits to a research paper, "Data Scientist" named one of the best new jobs in USA, capturing lightning in acrylic, the difference between Frequentists and Bayesians, how Nate Silver used Data Science to forecast the 2012 US election outcome and an electronic orrery.
As always, thanks for the comments and please send any suggestions to me firstname.lastname@example.org. Don't forget you can follow the blog using an RSS reader like Google Reader, or by following me on Twitter (I'm @revodavid). You can find roundups of previous months here.