What is the MSBA Capstone Project?
The Capstone Project is the culminating project of the MSBA degree program in which students develop a written business analytics consultancy plan and create an analytics solution or a proof of concept for an organization. Additionally, students will be required to record a video presentation of their final analytics project, communicating the impact and business value of their plan. Submitting and passing both the project (with a score of at least 3) and presentation (with a score of at least 2) is required for graduation.
Over the final nine months of the program, students will have the opportunity to apply the business analytics knowledge and skill set they acquire to create an analytics solution or proof of concept for a real or fictional organization of your choosing. During the project kick-off week, students receive a list of possible projects. The type of organizations and their projects vary—they can be in the private, public, or third sectors and could be located anywhere in the world. Students could also use their own employer or company as the subject of their project.
Students can complete this project either individually or in a group of up to six students. Important dates—including the Capstone Kickoff, Check-Ins, and submission deadlines for your Capstone project and presentation—can be found in your course schedule. You will receive more information about the project during the Capstone Kickoff week, as per your schedule.
Capstone Learning Outcomes:
- Conduct strategic analysis to identify analytics opportunities.
- Apply appropriate tools and methods to devise solutions for capturing analytics opportunities for their selected companies.
- Extract, analyze, store, and manage data to produce value.
- Assess the business value and impact of analytics solutions.
- Effectively communicate and collaborate with executive, technical, and non-technical audiences.
How much Python do I need to know for the MSBA Capstone Project?
Python is typically a useful tool for developing proof of concepts and analytics solutions, as it provides flexibility for data processing, modeling, and visualization. However, there is no strict requirement to use Python—you are free to choose the tools and technologies that best fit your project and team’s expertise.
The key is to be comfortable working with data-driven problem-solving approaches and collaborating effectively on analytics solutions. If Python is your preferred choice, having a basic to intermediate understanding of data manipulation (e.g., Pandas), visualization (e.g., Matplotlib/Seaborn), and potentially some machine learning (e.g., Scikit-learn) can be helpful. That said, depending on your project, other tools like SQL, R, Tableau, or cloud-based analytics platforms may be just as relevant.
Ultimately, the focus of the Capstone is on applying business analytics concepts to real-world challenges, so your ability to define a problem, select appropriate methodologies, and derive actionable insights is more important than expertise in any one programming language.