BUA 6310G - Business Analytics Capstone

Credits: 4

This course is the culmination of students’ learning - its intent is to offer students opportunities to apply the knowledge acquired in the program, in a directed, hands-on setting. As such, the course is a practicum built around solving applied industry data analytical problems, with the ultimate goal of giving students the opportunity to apply the knowledge acquired in the program. The course does not encompass any formal lectures, pre-determined assignments or examinations - instead, the student’s grade is wholly based on the successful completion of an assigned, individual project (students interested in sourcing their own projects will be allowed to do so, with instructor’s prior approval). The role of the instructor in this course is one of a coach, offering guidance and the overall project oversight for the duration of the project, but the key client stakeholders will also be asked to offer their assessment of the quality of the student’s project involvement and work. More specifically, once the project is started the student will assume all day-to-day project management and stakeholder communications, with the instructor serving as the project advisor, making sure the student is making satisfactory process, and providing any project-related guidance that might be needed. Lastly, although the exact scope and nature (e.g., exploratory data mining vs. predictive modeling) of each project will vary depending on client needs, each project will have to meet the following requirements:

A dataset to be used will need to be sufficiently informationally-rich, which means being made of - at a minimum - several hundred distinct records and 10+ variables
The contemplated analytical approach will need to fall under the general umbrella of multivariate analyses, and it will need to be focused on prediction, explanation or classification as focal outcome(s) and/or event(s)
The conduct of the project will need to encompass information gathering (i.e., determining and documenting client needs), analytic planning, data analysis, result interpretation, drawing inferences and making recommendations
A written, final report will be expected as one of the key project deliverables.