The course is structured around building, analyzing, and interpreting Excel-based financial models using real-world data sourced through FactSet. Students work with raw, messy datasets; learning to clean and standardize data for further analysis and to reformat or restructure it into usable inputs. As the course progresses, students visualize model outputs through sensitivity tables, scenario analysis, and charts; analyze financial data to extract meaningful signals about firm performance and value; and develop integrated three-statement models, DCF valuations, and LBO structures that estimate relationships among financial variables. This course requires students to communicate data-intensive work in written, visual, and verbal formats. In this course, student will product a Project Report, which requires a two-page equity research analysis that presents valuation results, sensitivity analysis, and financial highlights, supported by professional prose and structured exhibits in APA format. Students must translate complex model outputs (DCF intrinsic values, market multiples, and scenario tables) into a coherent written narrative supported by clearly labeled visual exhibits. The accompanying Project Presentation requires students to deliver those same findings orally in class, demonstrating the ability
to explain and defend modeling assumptions and investment recommendations to an audience.
Achieves technology student learning outcomes a,b, c, d, and e.

Approved for Data Intensive Course Designation starting Fall 2026.