60 Minutes aired a piece last night about scientific fraud at Duke University, where data was fabricated in order to support alleged discoveries in individualized cancer therapies. As a result of these investigations, a number of previously published scientific articles have been retracted. Less than a week ago, I highlighted an infographic from Jen Rhee
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Stephen Wolfram is doing it again. I’m a big fan of Wolfram (you can read some of my other posts here, here, and here…), and am always intrigued by what he comes up with. A couple of days ago, Wolfram launched his latest contribution to data science and computational understanding – Wolfram|Alpha Pro. Here’s an
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Jen Rhee has done some great homework on bad science and put them into a cool infographic that’s worth looking at. Here are some of the highlights from her research into bad science: 1 in 3 scientists admit to using questionable research practices 1 in 50 admits falsifying or fabricating data outright Among biomedical researcher
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Here are some interesting data science nuggets that I thought were interesting for a mid-January day… The first comes from TechMASH about data science being the next big thing. The primary nugget of note is that the supply of employees with the needed skills as data scientists – those people who really understand how to
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I ran across this article from the Independent today about the impacts of data algorithms, the ethics of data mining, and the future of our lives in an automated, data-crunching world. Below is a quote from the article by Jaron Lanier, musician, computer scientist and author of the bestseller You Are Not a Gadget. Algorithms
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This is the very question asked by Colin Hill, CEO and co-founder of GNS Healthcare, a healthcare analytics company. Hill hopes to make the case that healthcare can benefit from what a recent McKinsey report calls “the next frontier for innovation, competition and productivity.” I think Hill is onto something, especially with this insight: What will
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I ran across this interview by Fast Company with LinkedIn co-founder about his new book The Start-Up of You and the need for companies to have a data strategy, or risk losing “potentially a lot” in the future. Here’s that brief bit from the Hoffman interview: What do companies miss out on if they don’t have a
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Are banks predicting divorces? Well, if there’s data to help them predict such things, they may very well use it to optimize their business. Forbes has a couple of posts that peek into businesses use of “big data”. The first article talks about the race to build new analytics to solve challenges of large volumes
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You know that data science is truly becoming a recognized scientific discipline when billions of university dollars will be spent on its future. I wrote previously about Columbia’s effort to expand its Manhattan campus to build a data science and engineering center. However, Stanford and Cornell are also in the race. Much of this comes from
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Edd Dumbill is the general manager for the Strata Conference, recently wrote a nice post on Google+ titled “Why Do We Need Data Science?” Here is a really good insight from Dumbill and how data science applies to business: Why is the scientific method applicable to business and data? Every company’s business is complex in
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