Overview
The esports industry has grown from a niche community into a global entertainment category with significant advertising and sponsorship budgets. For brands and publishers deciding where to allocate sponsorship spend, the data landscape is fragmented — audience demographics, game genre trends, viewership figures, and sponsor-fit signals exist across different sources with no unified view.
This project was the final deliverable for MIT 5732, a graduate analytics course at the University of Oklahoma's Price College of Business. The goal was to build a Tableau dashboard that consolidates esports data into an analytical tool that could support sponsorship decisions — surfacing metrics on audience reach, genre momentum, and brand fit.
The Deliverable
The team produced a Tableau workbook (MIT_5732_Final_Project_Team_5.twbx) alongside supporting CSV datasets. The dashboard enables exploration of esports titles by viewership scale, genre, and sponsorship activity — structured to answer questions a brand or publisher would actually ask before committing a sponsorship budget.
Tools
- Tableau — primary visualization and dashboard tool
- CSV datasets — esports viewership, title, and sponsorship data
Team
This was a team of five, working within the MIT 5732 course at OU Price College. Team members: Ghulam Ali Doulat, Tsewang, Maldaaar, Ariana, and Michael.
What It Taught Me
The project was a practical exercise in the full analytics workflow: sourcing and cleaning data, deciding what questions the visualization should answer before building a single chart, and designing for a specific audience (brand decision-makers rather than data engineers). Tableau's strength is exactly this kind of exploratory, business-facing visualization — and working within a team of five on a shared workbook reinforced the importance of consistent naming conventions and clear chart labeling.