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Leading the way on big data

Ohio State students sitting in a classroom.Big data is big news these days. It promises to revolutionize all areas of human endeavor—ranging from the financial industry to the health-care industry, from the social sciences to engineering, and from scientific discovery to cybersecurity. This fall, The Ohio State University will debut an interdisciplinary undergraduate major in data analytics—the first of its kind in the country offered by a major research institution—to address a growing need for data analytics professionals. 

The College of Engineering is taking a leading role, along with the College of Arts and Sciences, in directing the new degree program and delivering the core courses in computer sciences, mathematics and statistics. Majors will receive a BS in data analytics from the College of Arts and Sciences.

“This collaborative and industry-responsive major in data analytics ensures that students will receive best-in-class preparation to become the next great Buckeye innovators in myriad fields,” said David B. Williams, Monte Ahuja Endowed Dean’s Chair and dean of the College of Engineering.

The data analytics program answers a strongly-articulated industry need for graduates with both quantitative computational and modeling skills, as well as critical thinking skills. Companies are seeking employees with acumen to not only build and query large data sets, but also to understand how to ask the right questions to extract critical, useable knowledge. 

“This area represents something that has grown up at the interface of business, computer science and engineering, especially engineering problem solving,” said David Tomasko, associate dean for undergraduate education and services. “It really is a very good example of something that requires interdisciplinary skills that come from many different points in the university.”

Engineering has a big role to play in data analytics—both as a fundamental piece of the burgeoning new field and as a consumer of data analytics technology. 

“When it comes to data analytics we all think of computer science, which focuses on how the data is collected, structured and accessed,” said Tomasko. “The real power of big data is in the ability to ask the right question and pose it in a way that you know the data can provide the answer. The engineering mindset can help with both of those critical elements.”

The core curriculum for the data analytics major provides a solid foundational footing; students will learn principles of data representation and big data management, software design and programming, and statistical modeling and analysis. General education requirements will provide students with the required skills to be able abstract, analyze and present actionable insights. A foreign language requirement addresses the fact that big data is an international field. 

Next, students will select courses in an area of specialization that will prepare them for experiential learning opportunities through partnerships with businesses. Specializations in biomedical informatics, business analytics and computational analytics are currently available. Other options, such as visual analytics, are likely to be added soon.

Like all Buckeye engineering students, data analytics majors will be required to complete a capstone or experiential component. 

“Our industry partners kept reiterating that we need to make sure students have not just the quantitative skills, but also the soft skills to be able to present actionable insights from the data,” explained Computer Science and Engineering Professor Srinivasan Parthasarathy, co-director of the data analytics major. “The experiential component is central to training students to be able to do that. Every student who graduates through this program has to have at least one capstone experience, and we expect that all of them will have had co-op or internship opportunities as well.”

In addition to going directly to work in industry, graduates of the new degree program will also be well-prepared to pursue graduate studies.

The major is aligned with Ohio State’s Discovery Themes Initiative, a ten-year, multi-million dollar investment in critical research in the areas of energy and environment, food production and security, and health and wellness

A foundational tool for tackling these challenges, data analytics is a burgeoning research area within the college, with applications and connections to virtually all of its major research thrusts. 

“From the design of new computer architectures and corresponding analytics algorithms, to deriving new ways to visualize massive, high-dimensional data sets and their underlying structures—the college is aggressively studying key big data issues,” said Associate Dean for Research Randy Moses.

Dozens of related research projects are underway across all areas of the college. At the Center for Electron Microscopy and Analysis (CEMAS), for instance, researchers are combining new approaches in electron microscopy with advances in visualizing high-dimensional data for applications such as understanding how materials crack and fail. Professor DK Panda (computer science and engineering) is deriving new computer architectures to handle massive data sets; Professor Joel Johnson (electrical and computer engineering) is conducting research on remote sensing and data processing of environmental data, which could help detect algae blooms in lakes or soil moisture levels; and Professor Ümit V. Çatalyürek (electrical and computer engineering and bioinformatics) is using data analytics to developed improved methods for identifying breast cancer. Meanwhile, Professor Scott Shearer (food, agricultural and biological engineering) is working on new remote sensing capabilities to understand crop health from UAV sensor data; and Professor Srinivasan Parthasarathy (computer science and engineering) is working to develop new ways to glean real-time insights from social media for disaster and large-scale emergency response.

The era of big data is here to stay and the Ohio State College of Engineering remains committed to developing the understanding, tools and talent needed to tackle the big data challenge.

Written by Candi Clevenger, College of Engineering Communications,