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.
Science/Technology/Engineering/Math (“STEM”) fields have traditionally been dominated by men. This is changing. Women 2.0 has an infographic on how women are catching up quickly to men in the STEM areas. (Women 2.0). Some headline numbers: 41 percent of Computer Science majors at Harvard are women That number is up from 28.9 percent just one year…
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…
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…
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
Here’s a nice piece from CNET on how big data alone is not enough, you really need the skills to know how to pull the meaning from it. That being said, it is getting easier to analyze big data. Money Quote: Last year, the McKinsey Global Institute projected that the United States alone needs 140,000…
Interesting piece in the MIT Technology Review about how big oil companies are using analytics on real time data to avoid spills and increase productivity, here.
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