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Art & Science Combined: Douglas Merrill On Humanizing Big Data Analysis
Big Data | April 24, 2013

Art & Science Combined: Douglas Merrill On Humanizing Big Data Analysis

"Data alone isn’t enough. People aren’t rational. Really." That's what Co-Founder and CEO of ZestFinance.com Douglas Merrill argues in a new article in Forbes. With the increased popularity of the big data movement, a common concern emerging in all industries is how to ensure that data is being harnessed and applied appropriately. One of the most important things Merrill says to keep in mind is the fact that simply mining and manipulating the data won't give you the whole picture. Nor, will it always give you the most accurate one. You must combine both math and science with intuition. A human element is needed to truly make sense of large data sets, or, as Merrill says, "art and science [must become] intertwined."

How does he do that with his team at ZestFinance? He doesn't just look for people who "speak data science." Diversity in your team is key to getting a holistic view of the data at your disposal. "Look for people who love data, and have their own—unique—way of looking at it," he says. A diverse team brings multiple different approaches to understanding and implementing data, he also argues. "Although there are statisticians and computer scientists, we also have psychologists, physicists and theoretical mathematicians," he tells Forbes. "Each of these disciplines views the world differently, brings different techniques and, hence, illuminates the data in different ways."

Since the core product of ZestFinance is data and numbers, but the core consumers are people, it makes sense to combine multiple disciplines in order to meaningfully convey information. Where computers need help pinpointing the significance of data-derived correlations, humans need help from computers to overcome their own personal biases surrounding those correlations. In his forward-thinking articles and keynotes, Merrill explores how companies can champion cultures of innovation within their ranks. And, as he explains in this article, part of that stems from incorporating the human element into science and math—and letting computers pick up where the humans leave off.
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