Data Science Education Gets Visual

In 2010, there were a total of 131 confirmed, full-time business analytics university degree programs, including 47 undergraduate-level programs. When I wrote an article on this topic in 2017, that number had more than tripled at 564 programs, including more than 50 undergraduate programs, nearly 100 certificate programs, and close to 400 master’s programs. As of April 2019, the numbers were even larger. The numbers had grown to 59 verified undergraduate programs, 101 verified certificate programs, a whopping 420 master’s programs, and 23 doctoral specializations for a total of 603 verified programs globally.

As business analytics education, including specific instruction in data visualization, becomes more solidified in higher education, the question is not: “Are we teaching business analytics?” but instead becomes: “What are we teaching in business analytics?” To make education most valuable, it should align with what the market is looking for in potential job candidates.

The Rise of Data Visualization as a Desirable Skill

In an IEEE paper published earlier this spring, my fellow researchers and I studied the trends of industry job postings for business analysts, focusing primarily on the field of data visualization practitioners. Not only did we find that since 2010 there has been a 1,500% increase in job postings listing data visualization as a desirable skill, but also that the demand is expected to continue growing in 2019 and beyond, making data visualization one of the hottest areas of job growth and academic opportunity.

Paired with data visualization, employers specifically sought candidates with experience in SQL (51%), Tableau (41%), Microsoft Excel (34%), Data Analysis (31%), and Python (30%). Beyond technical abilities, they want software prowess. Of note was their interest in Tableau (41%), Excel (34%), and SAS (22%). Other non-technical skills included such quantitative skills as communication skills (47%), research (37%), writing (32%), teamwork/collaboration (31%), problem solving (30%), and general project management skills. While it may seem obvious that most employers want employees to communicate effectively, these postings specifically mention this and highlight communication and qualitative abilities requisite of jobs in analytics and data communication. This reflects an increased focus on visual data storytelling as a new skill that is an aspect of data visualization.

A Focus on Best Practices and Other Skills

This statistical information on industry demand gives us a sharp view into what we should be teaching—and learning—in this growing cohort of analytics degree programs and a yardstick by which to evaluate them. An appropriate class for professional students should focus not only on the underlying principles and best practices of data visualization, but should also include training on other skills, such as software specialization.

While exact curricula and approaches are up to individual schools, educators interested in designing courses appropriate for professional students should provide education on data visualization best practices in terms of graphics as well as visual cognition so that students know what the different types of charts and graphs mean, how they are used to represent data, and how to appropriately communicate insights.

No Longer Limited to Research

Visual design principles should also be taught as a foundation for how to apply elements such as color, shape, and visual hierarchy in data visualization charts, dashboards, and stories. These concepts can and should also be incorporated into a more traditional visualization class to help the students apply advanced programming concepts within an industry setting.

No longer limited to a research area, data visualization is an integral skill of business analysis.


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