College - Author 1
College of Engineering
Department - Author 1
Industrial and Manufacturing Engineering Department
Degree Name - Author 1
BS in Industrial Engineering
College - Author 2
College of Engineering
Department - Author 2
Industrial and Manufacturing Engineering Department
Degree - Author 2
BS in Industrial Engineering
College - Author 3
College of Engineering
Department - Author 3
Industrial and Manufacturing Engineering Department
Degree - Author 3
BS in Industrial Engineering
Date
12-2019
Primary Advisor
Tali Freed, College of Engineering, Industrial and Manufacturing Engineering Department
Additional Advisors
Xuan Wang, College of Engineering, Industrial and Manufacturing Engineering Department
Abstract/Summary
This paper explores economic solutions for Formula 1 racing companies who are interested in data visualization tools. The research was conducted on the current development of data gathering, data visualization, and data interpretation in Formula 1 racing. It was found that a large chunk of racing companies within the league needs an affordable, effective, and automated visualization tool for data interpretation. As data collection in Formula 1 arises, the need for faster and more powerful software increases. Racing companies profit off-brand exposure and the more a racing team wins, the more exposure they receive. The goal of the paper focuses on solving the issue of data visualization. It begins with the current state of Formula 1 and the background of the billion-dollar industry. Then, the criteria needed for an effective solution is discussed and is used to measure three different software solutions. The three solutions considered were Tableau, Power BI, and Python. Python earned the highest rating according to the criteria of process time, scalability, usability, customizable, and cost-effectiveness. As proof of concept, a demo was created using Python, specifically using the Python framework Dash, showing the simplicity and versatility of the software. Racing companies looking to save money should consider implementing Python into their data visualization to increase their odds of winning and rising in the rankings.
URL: https://digitalcommons.calpoly.edu/imesp/254