Michael Kowelenko, N.C. State, at IBM Information on Demand 2013 with John Furrier and Dave Vellante @thecube #IBMIOD Michael Kowelenko, an Assistant Professor at North Carolina State University, discussed decision making in the age of Big Data with theCUBE co-hosts Dave Vellante and John Furrier, live at the IBM Information on Demand 2013 event in Las Vegas. Kowelenko explained that while the focus was once on how data came together, and how we looked for aggregation of information through analytics, decisions needed to be made at the end of the day. The university works with students and companies on how to do critical thinking to support future decision making. “The technology has really evolved with what we can do. There’s all this new data,” which is not really new, Kowelenko explained. “You now have ways to capture that data.” There is a need to take unstructured information – which is 80/90 percent of all information out there, and figure out how we can extract knowledge from that. With Hadoop companies have the ability to spread their work over many machines to take in that information in, “we have tools to extract that information, we can apply context to extract the data we need,” he said. Even with social data, it existed, but we could not capture it before. With social data, Kowelenko noted, “in a sense, I understand what’s going on with it,” but we still have to understand “why did it happen, how can I change outcome based on it.” In data we trust Commenting on gut feelings as a basis for decision making, Kowelenko said it was a misinterpretation of a gut feel. What is perceived as such, is really experiential based, there is an anchor in data. “You have a capacity of taking in that information, what you want to do along with the gut feeling, is augment it with these tools.” As we collect more data that we can analyse, we can de-risk decision making. “Data is one aspect of the thing, in decision making the bigger aspect is culture,” Kowelenko said. All the data in the world cannot change a cultural thing. “You can make better decision with data, but will you be allowed to?” Asked to comment on the idea of everyone being a data scientist with the right tools, Kowelenko said that in business school, people were trained to be data managers, understand the technology and leverage it to make better decisions. “We need you to know how to ask a good question and extract the data to answer it. You need to know how to converse to data scientists” to get the data to you. . . The university first teaches students about critical thinking. In critical thinking, one of the first things you look for are bias and alternatives. “Once you are able to do that and understand the core of the problem, you can break it down and use to the data to support or refute your position.” The future of scientists + machines Asked what he would recommend to young people in high school or those considering career changes and looking into data science, Kowolenko said it started with an interest in problem solving. “Do you like problem solving? If you like it, you will like a career where you put data together and solve puzzles. If you’re naturally curious and you want to find out why the things work the way they do, Big Data is the right career choice.” Commenting on the future of decision support, Kowolenko said the most interesting challenge is deciding “how much do you want the machine to do vs. how much do you want the human to do.” While the machine should do more of the heavy lifting, human should focus on the decision making part and be less worried about getting the information in.”