Acceso usuarios
Estados Unidos
In an effort to expand data analytics instruction, universities have launched data analytics majors and graduate programs in data analytics. While this effort meets the need for developing data analytics specialists, an equally important need is to improve the data competencies of undergraduate business students who do not major in analytics but still need to have competencies with analytics. However, business students not majoring in data analytics have limited credit hours available for data analytics. Therefore, it is necessary to select data analytics topics that meet employers' needs. We hypothesized that surveying industry advisors would help us revise the current curriculum to incorporate data analytics learning objectives that are both necessary and sufficient. The results showed that the most important data competencies are basic spreadsheet skills (86%), intermediate spreadsheet skills (82%), retrieving relevant data (86%), documenting data (92%), and presenting data (96%). The least important area is teaching software programming to non-analytics majors (14.5%). As a result of this study, we were able to develop a new curriculum to meet employer needs by revising previous courses without increasing required credit hours.
