One School's Curriculum Gets an Analytics Upgrade

The University of South Carolina prepares undergraduates to handle the deluge of data that's coming their way.
Deriving Meaning from Data

To provide companies with the talent they’ll need to make sense of their data, the Darla Moore School of Business at the University of South Carolina in Columbia has significantly expanded the teaching of analytics in its undergraduate core curriculum. This expansion includes required statistics courses at the freshman and sophomore levels, as well as a business analytics concentration. In the spring of 2018, the school also piloted the teaching of R, a widely used opensource computer language, instead of Excel to analyze data in its core statistics courses. R training now has become a mandatory part of the curriculum.

Starting in 2018, all 5,200 of its undergraduates must complete capstone projects using R to analyze real-world business data in the school’s just-opened Data Lab. Students have opportunities to work with popular tools such as SQL to learn database management and Power BI to visualize and report data. Tableau, another powerful data visualization tool, is being taught at the graduate level.

The objective is not necessarily to train students to become data scientists, but to equip them with the tools to understand how to draw accurate conclusions from the data, says Peter Brews, the Moore School’s dean. “We have to train our students to analyze that data and move it from data into knowledge that leads to better decision making.”


Students are first exposed to R in their sophomore statistics class. They still learn to use Excel—however, they use R to clean up imperfect data with missing values and errors, manipulate and analyze data, and create customizable graphical displays not possible in Excel.

Most of the school’s 1,400 sophomores have never worked with computer code before, and they might not have expected analytics would be part of their business educations, says Leslie Hendrix, the assistant professor who is coordinating the statistics course. Students who are more familiar with menu-driven software are often intimidated by R’s code-writing interface. To ease their way, the school has created video tutorials and other tools and makes those resources available across all course sections.

It’s important that students learn to use these resources to troubleshoot code and overcome error messages for themselves.

It’s important that students learn to use these resources to troubleshoot code and overcome error messages for themselves, says Hendrix. “I often tell them, ‘You can’t just watch me to do this. Can you learn to swim by watching someone else swim?’” Once students establish baseline abilities with R, she adds, they don’t just have “a heavy-hitter skill” to put on their résumés. They also have developed an aptitude to learn new computer languages throughout the rest of their coursework and careers.

To help faculty keep their skills upto- date, the school provides them with the same online training resources it offers students, as well as the Data Lab, internal workshops, and external professional development opportunities.


Students put their skills in R to work in the Data Lab for the final project of their sophomore statistics class. Their challenge is twofold. First, they must clean up an imperfect and incomplete real-world data set; second, they must use that data to create a predictive model that holds true when applied to another portion of the data set that has been withheld.

During the project’s first run, student teams used tools of their own choosing to analyze data involving local real estate prices to predict actual sale prices of homes. Students who used R fared much better in the challenge than those who used Excel, says Hendrix. In addition, students were encouraged to use resources outside of the class to teach themselves new skills.

As the project progressed, each team’s predictions were posted and ranked online, with the leaderboard constantly updated as teams submitted their answers. “Students said that they became obsessed with it,” says Hendrix. Patrick Nealon, who was part of the pilot class, believes he landed a commercial real estate internship as a result of his knowledge of the language. “Knowing how to use R was one of the main reasons I got the internship. It is so refreshing to learn something that I will be able to use outside of the classroom.”


After they complete both statistics courses, students will continue to study analytics for the remainder of their undergraduate careers. Faculty are currently adjusting syllabi for upper-level courses to include opportunities for students to use their skills in R in other ways.

Undergraduates who wish to delve into analytics more deeply can complete the school’s new business analytics concentration by taking four classes beyond the required core courses. These include an additional class in data analytics that covers database management, SQL programming, and data visualization; and three electives that focus on analytics in particular fields. Every major at the school—including accounting, finance, economics, management, and marketing—has at least one elective that applies to the concentration.

Since the analytics concentration was introduced in 2015, it has become more popular among undergraduates than any other undergraduate concentration or minor at the Moore School. In just one year, enrollment in the concentration has increased from 100 to around 310 in the fall of 2018.

By the fall of 2019, it’s possible that number will increase to 500, says Brews. He adds, “I’m hoping eventually every Moore School student chooses to do the analytics concentration.”


In delivering its curriculum, the school works closely with its corporate partners, which are quickly becoming regular customers of its students’ skills. These include Nephron Pharmaceuticals, based in Columbia, which is using data analytics to examine every aspect of its operations, from manufacturing to marketing. The company wants to better evaluate its performance, find greater efficiencies, determine what processes are creating production bottlenecks, and identify which sales efforts are bearing the most fruit, says its CEO Lou Kennedy.

Recently, Nephron assigned a Moore School alumnus to analyze its contracts to ensure that its outgoing payments matched contract requirements. The graduate identified mistakes and overpayments— including one error that would have cost the company US$85,000. In total, the graduate saved the company $850,000 in just one year.

Kennedy now participates in the Moore School’s career fair days every year, even when her company does not have immediate openings. The event, she says, is an opportunity to discover how students might apply their analytics skills to help the company in ways she has not anticipated.

“It’s a data-driven world we live in,” says Kennedy. “I recognize the value of these degrees, and I like what I see.”

Mike Fitts is a freelance writer based in Columbia, South Carolina.

This article originally appeared in BizEd's January/February 2019 issue. Please send questions, comments, or letters to the editor to [email protected].