The Department of Business Analytics and Statistics introduced a cutting-edge course in big data this spring for its MSBA students. Co-taught by Dr. Russell Zaretzki and industry experts from Oak Ridge National Laboratory and a national consulting firm, the course focuses on giving students a working knowledge of big data tools such as Hadoop, Spark and NoSQL databases.
Students will explore the possibilities of data mining, evaluating huge information sets and going to the cloud level to analyze the data. “They won’t be coming out of the class as experts, as that takes quite some time,” says Zaretzki, “but they will become familiar with the tools, know their purposes and how they’re used, and be able to move forward quickly in the future.”
To create the highest potential for relevant learning, the department decided to hire adjunct industry experts to co-teach the course. “Knoxville has a lot of expertise in big data and computing,” Zaretzki says. “We’re using experts from both the industry and ORNL to help teach the class. Having them on board will help students gain hands-on experience using these big data systems.”
One of the instructors, Dr. Byung H. Park, works on supercomputing teams at ORNL, using analytics to understand system performance. “The computers are so huge, they spit out all kinds of information,” Zaretzki explains. “Park uses these big data tools to understand what those computers are doing and if they’re performing correctly.”
Dr. Thilina Gunarathne, specialist director, data science and engineering at KPMG, is the other industry expert. Gunarathne manages a large Hadoop infrastructure for big data analytics and supports some critical big data projects.
Drew Schmidt, a graduate research assistant in UT’s Department of Business Analytics and Statistics and an expert in the intersection of mathematics, statistics, and high performance computing, will also assist Zaretzki with the course.
“This course is pushing us forward,” Zaretzki says. “The idea is to bring students the next level of computing skills compared to most of our previous analytics courses. We’re positioned between business analytics and computer science—it’s much more hands-on and hard-core, and the tools aren’t as user-friendly, but people working in big data today have to be able to work in this less user-friendly, more expert environment.”