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DNSC 6217, Business Analytics Practicum

From 2019 through 2022, Brian taught The George Washington University's Business Analytics Practicum class, DNSC 6217. In this one-semester course, students will work in teams on an “client project”. The project is provided by one of our advisory board partner firms and will entail working closely with the firm’s “project sponsors” over the semester and presenting findings to them at the end of the project. Students will have access to real data and work collaboratively with specifically designated mentors at the organization with which they work. The practicum is designed to apply the knowledge gained in the classroom to real-world problems. The experience is designed to allow students to develop deep expertise in a set of analytical tools and business and communication skills required for the successful completion of analytics projects in the real world. 

After completing this course, the student should be able to showcase the following abilities:

  • Design, develop, and execute a data-driven investigation
  • Frame a data-driven study based on the client’s requirements and the available data
  • Identify the value propositions for the project and the appropriate questions that will guide your project
  • Document and describe the trade-offs involving the data, its quality and availability, and depth of analysis, and available resources
  • Convey project deliverables in different modes (at least two -- one for academic requirements and one for project sponsor)

As a graduate of The George Washington University and a practicing analytics professional for over 30 years, Brian enjoys sharing real-world experience in an academic environment. Brian continues to support education in the field of business analytics through his role on the GW MSBA Advisory Board and the employment of teams of interns for business analytics research projects. If you are interested in discussing supporting the practicum class as an industry sponsor, feel free to contact Brian.

Sample Projects...

  • Anti-Corruption Analysis to provide expanded capabilities to shape future anti-corruption investment. 
  • Consumer Banking Customer Analytics to develop a model that predicts business activity at consumer banking branches. 
  • Internet Due Diligence and Entity Risk Rating Tool development of an automated tool that replaces the human in performing internet due diligence.
  • Credit Loss Forecasting Model for credit risk and regulatory purposes.
  • Insurance Risk development and understanding of the insurance risk profile for a global insurance company, including identify ways to best mitigate instances where their risk profile is outside of their desired risk appetite and tolerance.
  • Predicting Student Success in terms of determining what attributes can colleges measure in incoming students to identify students that need additional support to be successful after graduation. 
  • Extreme Weather Monitoring for Emergency Management and Disaster Planning
  • Healthcare claims fraud to help identify fraudulent patterns in healthcare data to stop fraud before it happens.
  • Monitoring foreign language media coverage to identify key issues and sentiment. 
  • Targeted marketing analytics to determine specific elements of outreach that lead to campaign success. 
  • Sports analytics to determine specific elements of professional sports teams that increase franchise revenue and profit.