Across industry and academia, the past several years have seen a proverbial explosion of new business analytics education programs.
If you’re new to the analytics labor market—or looking to advance your credentials—academia has likewise undergone a period of massive innovation as educators work diligently to keep pace with market demands and produce a new breed of business analytics education. The change has been nothing short of astonishing: In 2010, there were a mere 131 confirmed, full-time business intelligence/business analytics university degree programs, including only 47 undergraduate level programs, spread nationwide. From these meager beginnings, the availability and diversity of new academic programs eager to teach students of all levels have reached incredible levels. Today, there are more than 500 undergraduate, graduate, certificate-based, and post-graduate programs designed to serve both professional and research students on campus and online. In addition to the myriad programs offered by accredited U.S.-based universities, many more are available internationally.
Beyond the challenge of producing entire new programs to better prepare students for success in the analytics industry, educators have also been tasked with ensuring that individual courses sufficiently provide students with the skills, technical competencies, and hands-on abilities that make up the cadre of sometimes unclear and always fluctuating skills required by today’s highly competitive and evolving job market. This is no easy feat.
One skill that continues to bubble to the top—especially in a world of big data and even bigger insights—is data visualization. However, as a discipline, data visualization is vast, consisting of many different areas and even more different interpretations.
One approach to aligning expectations between industry and academia is by studying the skills—and combinations of skills and software—companies are looking for in their applicants. A recent study of job postings between March 2017 and February 2018 found a total of 30,786 nationwide that required “data visualization” as a skill (up 17.6% from the preceding annual period). These jobs, all of which demanded at minimum a bachelor’s level education, required applicants to also have “specialized” skills including working knowledge in SQL (51%), Tableau (41%), Microsoft Excel (34%), data analysis (31%), and Python (30%). Although there is some overlap between what is listed as a specialized skill and what are listed as skills regarding proficiency with preferred software packages, about 41% of data visualization-related jobs specifically looked for candidates with experience in Tableau, while other common software included (in order) SAS, Oracle, Business Objects, Qlik, Spotfire, and SAP.
Today’s data visualization students will benefit from learning both the underlying principles and best practices of data visualization, along with the most in-demand tools and software packages in which to apply them. Exact curricula and approaches remain, of course, up to the individual schools. However, students should be tasked with (and prepared for) learning the entire visual analytics process end-
to-end—from data acquisition to preparation to analysis to visualization and communication of visual methods such as reports, dashboards, and visual data stories. Ultimately, keeping tabs on what’s happening in the analytics market, and applying that toward how courses grow and evolve over time, will ensure that the next analytics experts are equipped to practice their learning in a way that’s meaningful once they leave the classroom and enter industry.