When it comes to getting a job, the USA has bifurcated into two employment worlds, the digital world and the brick and mortar world.

The brick and mortar world is everything you physically touch. Its manufacturing. Its retail sales. Its distribution. Its construction. Etc.

The digital world is everything defined by what you find on computing devices. It can be on your desk, in your hand or in the cloud.

What has happened is that the brick and mortar world has had every bit of intelligence that can be sucked out of it completely removed.  Any information that can be created, identified or recognized is being captured in as automated a process as possible and delivered to “big data” or even small data databases in the cloud. What used to require some intelligence at the brick and mortar work place has been seeded and ceded into the cloud.

Every smart…

Which country wins the Olympics? Right now China is in the lead for most medals (73: 34 gold, 21 silver, 18 bronze) and most golds. The USA is second in both categories (71: 30 gold, 19 silver, 22 bronze). In 2008 there was some controversy about whether the ranking should be done by largest total number of medals or largest golds; here’s the table from Wikipedia. If I recall correctly (though it’s surprisingly hard to search for this) non-Americans were saying that the “right” way to do it is by golds, but Americans insisted on doing it by total medals. Not surprisingly the USA had the most total medalists in ’08 (110, to China’s 100) but not the most golds (36, to China’s 51).

But it hardly seems fair to expect, say, France to get as many medals as the USA, simply because they have about one-fifth the population…

If you are interested in this data set you might like my latest post where I use it to make book recommendations.

This one came about because I was searching for a data set on horror films (don’t ask) and ended up with one describing the links between philosophers.

To cut a long story very short I’ve extracted the information in the influenced by section for every philosopher on Wikipedia and used it to construct a network which I’ve then visualised using gephi

It’s an easy process to repeat. It could be done for any area within Wikipedia where the information forms a network. I chose philosophy because firstly the influences section is very well maintained and secondly I know a little bit about it. At the bottom of this post I’ve described how I got there.

First I’ll show why I think it’s worked as a visualisation. Here’s the…

Last night, my dear friend George Casella passed away, after a long illness he had fought with his usual determination and optimism. Having known George for 25 years, I am devastated… He was a great father / friend / collaborator / researcher / teacher / editor / runner, and, above all, a great and unique person. The loss is profound, the loss is significant, for me and for us… My thoughts go out to his wife, Anne, and children, Benjamin and Sarah, who are the ones to feel this loss the most keenly.

(The following is adapted from a recommendation letter George asked me to write when he was considering moving to the University of Florida, Gainesville, from Cornell, a task for which I considered myself completely inadequate. I just hope it carries some of the love and admiration I felt for George.)

To me, George was the…

Here’s something I started to write a few months ago, but never got around to finish it off.

Neil Charles over at Wallpapering Fog has just written an excellent post about the growing importance of R and Tableau to the modern day analyst. Although not as old in the tooth as Neil (sorry Neil), even in the last 5 years, there has been a definite movement towards a much wider skill set for everyday analysis, at least within marketing.

The days of only using the likes of SPSS, SAS and Excel are long gone as the need to make work more repeatable, scalable and downright flexible. Today’s analyst needs to be comfortable getting hold of new datasources that don’t necessarily sit in an excel file or in tabular form, manipulating it, using a statistical technique that they didn’t necessarily learn at university and then visualising the results (maybe on a…