Friday Roundup: What Interested Us the Week of January 26, 2015
Microsoft buys Revolution Analytics
Janet Kamin, 1/30/15
The biggest news in data science this week is the purchase of Revolution Analytics by Microsoft. Revolution Analytics is a company built around commercial software and support for the popular R statistical computing project. So this is a signal that Microsoft is looking to enter into the data science field. Among Revolution’s contributions to the R world is engineering it to run across systems like Hadoop. So Microsoft is not only entering into data analytics, but into Big Data in a big way. Joseph Sirosh, Microsoft’s corporate vice president for machine learning says in his blog, “companies need to reduce the data science and analytics skills gap inside their organizations, so more employees can use and benefit from R. This acquisition is part of our effort to address these customer needs”. The question remains how much this will change the Revolution Analytics we’ve come to know.
Watching the ads! That’s what many of us think about when we think about Super Bowls, and what many of us talk about. Turns out, big data is watching. And two key pieces of information may change the way Super Bowl ads are delivered to us. Studies of tweets indicate that people talk more about the games after they are over, than while ongoing. This makes sense. It also turns out that only about 20% of the ads result in increased sales. So why not change how things are done. The idea suggested by Akshay is that more investment will go into mobile ads - Super Bowl ad money on mobile devices, and continuing after the game is over - when people are talking about is. Time will tell if this prediction is accurate.
Steve Lohr 1/27/15
Can you imagine bankers making lending decisions based on character, current performance or future promise? Like they used to? Well it’s back to the future for Louis Beryl and his San Francisco start-up, Earnest. They make loans to the underserved - people who might be great credit risks, but because they do not have any credit history have a hard time getting loans - or have to pay more. That is, young people. Using data science to develop algorithms that include those aspects of banking that went out with our grandparents’ generation, Earnest announced this week a $17 million round of series A funding. So far they have raised $32 billion
Derrick Harris 1/23
Hilary Mason, founder of bit.ly and a leading voice among data scientists, was on the Structure Show podcast this week. She discussed what she’s excited about and why data science is a legitimate field. There’s a new trend towards some skepticism, even derision, about what data science can do. And a little cynicism as big technology companies promise their machines can replace what the data scientist does. Hilary spoke to these trends. “You have math, you have programming, and then you have what is essentially empathy domain knowledge and the ability to articulate things clearly. So I think the title is relevant because those three things have not been combined in one job before. And the reason we can do that today, even though none of these things is new, is just that the technology has progressed so much that it’s possible for one person to do all these things — not perfectly, but well enough.” You can hear her whole talk by going to the link above.
James Kobielus, 1/30/15
There’s been much talk of late of the inevitability of the Chief Data Office Science Officer coming into its own - a corner office right next to the CEO. But how does this jive with the role of CIO? Renette Youssef asserts that Chief Data Scientists will "hold the purse strings when it comes to key IT buying decisions that leverage company data”. James Kobielus argues the opposite. There is a clear demarcation between hardware and software and the CIO position will continue to be critical to the health of any organization.