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The Schumpeter column in the current edition of The Economist is on how the revolution of big data and analytics is changing the landscape of business:

One of the key data analysis tools that the BellKor team used to win the Netflix Prize was the Singular Value Decomposition (SVD) algorithm.

Last month's R/Finance 2011 conference in Chicago was an outstanding event, bringing together some of the best minds in applying R to financial data. Presentations from the speakers are now available for download, with a wealth of useful information there for anyone working in quantiative finance. Not to be missed, though, is John Bollinger's (yes, that John Bollinger) retrospective on the history of computational finance.

The May/June issue of Washington Monthly has an in-depth feature article on Edward Tufte, the data visualization guru. Tufte's a personal hero of mine: Bill Venables introduced me to his first book, The Visual Display of Quantitative Information, when I was an undergraduate.

Online training provider Statistics.com has introduced a couple of new R-related courses which are well worth checking out. These are all self-paced on-line courses, with materials by and interactive feedback from leading R gurus. Current R users looking to take their programming skills to the next level will be particularly interested in the Advanced Programming in R course from Hadley Wickham. Hadley has shared a cracking set of course materials for Advanced Programming in R, so you can see what's covered.

I was sad to have missed last week's OSBC (Open Source Business Conference).

This post from Stephen Weller is part of a series from members of the Revolution Analytics Engineering team. Learn more about the RevoScaleR package, available free to academics as part of Revolution R Enterprise — ed.

The most recent KDnuggets poll asked, "Which data mining/analytic tools you used in the past 12 months for a real project". Amongst all commercial and open-source tools, open-source R was the second most-frequently cited, by 23.3% or about 1 in 4 respondents.

The latest prediction competition at Kaggle is literally "out of this world": the goal is to quantify the shape of 2-D images of galaxies from a simulated telescope, to test models for how invisible dark matter in the Universe distorts the images through gravitational lensing (as shown in the image below; see the FAQ for more details).