and was only off by 400,000 on the popular vote. How ya like big data now? VentureBeat has the story. (VB) See out previous coverage of Nate Silver here.
and was only off by 400,000 on the popular vote. How ya like big data now? VentureBeat has the story. (VB) See out previous coverage of Nate Silver here.
Tom Davenport has an excellent mid-lenth piece out in the Harvard Business Review about how data science is the new sexy job. Tom has been writing about this for quite some time. (HBR) Of particular note was his description of the Insight Data Science Program, which is a post-doc Silicon Valley feeder five week training…
Here’s a piece from the Center for Digital Eduction about how predictive analytics are making inroads into the slow moving world of college education. The impetus is cost savings and graduating students in four years. The upshot: an algo might match you up with certain professors/classes.
Sports Illustrated had a short but entertaining article on Nate Silver, which can be found here. Silver is a predictive savant and has been turning his powers to all manner of events. His political blog can be found here.
Steve Lohr had a typically good piece in The New York Times on how database hardware is catching up to analytics software and how the results will be powerful. You can read the article here. Some think this represents a one of those discontinuous leaps in computing equilibrium. Here’s the money quote: Advances in such…
The FINRA Investor Education Foundation website has some interesting, if limited, analytic offerings for individual investors to to see if they are vulnerable to scams and investment fraud. The analytic offerings can be found here.
In a story that we have been following for some time, farmers are utilizing big data analytics to reduce their uncertainty. See the siliconAngle story here. Of note is the company Farmeron, who offers a web-based analytics service.
In a Forbes article dripping with irony, the question is asked: will data science eliminate data scientists? It seems unlikely to me, although I do believe the lower end of data science will become widely distributed. You can read the article here. My worries about AI involve Skynet going live.
CIOInsight is out with this list. I’m not sure of the methodology, but it’s interesting. See the piece here. 1. San Francisco 2. McLean, Virginia 3. Boston 4. St. Louis 5. Toronto
SmartData Collective has a nice entry-level piece on thinking about decision management here. The cheat sheet: 1. Implement rules and observe closely, then lather, rinse, repeat. 2. Measure constantly. 3. Look beyond your KPIs (key performance indicators) for what they aren’t telling you. 4. Be creative. (Easier said than done). 5. Evaluate your results from…
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