Thought Leaders in Big Data: Interview with Sasha Gilenson, CEO of Evolven (Part 1)

Sasha Gilenson is the CEO and co-founder of Evolven, a leading company in IT Operations Analytics. Prior to Evolven, Sasha spent 13 years at Mercury Interactive, participating in the establishing of Mercury’s SaaS and BTO strategy. He studied at the London Business School and has more than 15 years of experience in IT operations. In this interview, Sasha talks about how Evolven solves issues in companies’ IT operations and gives insights into the history and future of big data.

Sramana Mitra: Sasha, let’s start with some context about Evolven. Tell us what you do, how long you have been in business, and what size your company is.

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Thought Leaders in Big Data: Interview with Jeremy Howard, President and Chief Scientist of Kaggle (Part 5)

Sramana Mitra: Who are these people? What is their motivation to participate in this contest? Of course, this is all very time consuming. Thousands of people can be doing this on their own time. There must be something going on in the psychology that you have studied and understood. What is that? >>>

Thought Leaders in Big Data: Interview with Jeremy Howard, President and Chief Scientist of Kaggle (Part 4)

Sramana Mitra: It is fascinating and fun what you are talking about. But let me understand the framework of how these are done. First, who is sponsoring the prize money, and who is providing the data?

Jeremy Howard: The same company in both cases – Heritage Provider Network. This network is run by Dr. Richard Merkin. Dr. Merkin is a visionary guy. He has been very successful in business, he is aware of the challenges in the U.S. healthcare industry, and he believes that the use of data could lead to much better health outcomes. His company – his initiative – is both making the data available for the competition and making the $3 million prize available as well.

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Thought Leaders in Big Data: Interview with Jeremy Howard, President and Chief Scientist of Kaggle (Part 3)

Sramana Mitra: What about the data repositories on which these algorithms are being run? Is that still fitting inside corporate data warehouses, and R software plugs in to them?

Jeremy Howard: The hard thing generally is training the algorithms, not so much running them. Training the algorithms basically is oversimplified – it is coefficients in an algorithm. Once you figured out what they are, what you are left with is a very simple mathematical formula. >>>

Thought Leaders in Big Data: Interview with Jeremy Howard, President and Chief Scientist of Kaggle (Part 2)

Sramana Mitra: What did you do with that compensation? Did you want to make it available to everybody? When did it get started with Kaggle?

Jeremy Howard: Kaggle was started by [CEO] Anthony Goldbloom. I was the next guy involved. Anthony had been working with the Economist magazine and big data stories. Then he realized there was a huge demand for analytics in organizations, but also a lot of money involved in creating big data infrastructure. Very few people were getting much value out of this. He had a hypothesis that competitions would be a good way to engage the communities and engage the best people to solve these problems. As it turns out, his hypothesis was correct.

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Thought Leaders in Big Data: Interview with Jeremy Howard, President and Chief Scientist of Kaggle (Part 1)

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Jeremy Howard is president and chief scientist at Kaggle, and sits on the faculty at Singularity University. Previously, he founded FastMail (sold to Opera Software) and Optimal Decisions (sold to ChoicePoint, now called LexisNexis Risk Solutions). Prior to that he worked in management consulting, at McKinsey & Company and A.T. Kearney.

Jeremy’s passion is applying algorithms to data. Kaggle is the world’s largest community of data scientists – more than 75,000 at last count. Kaggle’s data scientists have solved some of the toughest problems for some of the world’s smartest organizations, including NASA, Merck, Ford, Allstate, and Wikipedia. At Singularity University, Jeremy teaches data science to the elite group of students who are awarded places to the graduate program.

At FastMail he used algorithms to automate nearly every part of the business – as a result the company only needed a total of three full-time staff, and got over a million signups. Optimal Decisions was a business built to commercialize a new algorithm he designed for the optimal pricing of insurance.

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Thought Leaders in Big Data: Interview with Oliver Downs, SVP of Data Sciences, Globys (Part 5)

Sramana Mitra: What is your estimate of the visualization side of the equation? What tools and technologies are you using in your work from the visualization tool kits?

Oliver Downs: That is a good question and also always a challenge. Making sure that the findings you have are accessible to the type of customer you have. With our business, our sale is not to the CIO, it is to the CMO’s organization. We have been making use of some of the advances in dynamic Java Script – D3 – as a good example. From an ad hoc perspective, we use some of the interactive tools that are available on Typhoon [Map]. Prototype visualizations are getting them out there quickly and allowing us to get interesting feedback on them and then perhaps bring them into a more elegant and sophisticated looking visual experience using D3. >>>

Thought Leaders in Big Data: Interview with Oliver Downs, SVP of Data Sciences, Globys (Part 4)

Sramana Mitra: Let me ask you a definition question: How do you define big data? Business analytics has been around for a long time. A lot of what you are doing has been around for a long time in other business analytics formats. How do you define the difference between what is happening in the more generic analytics business world and in big data? What is the differentiating factor? >>>