Analysis of University Fitness Center Data Uncovers Interesting Patterns, Enables Prediction

Data is increasingly being used to make everyday life easier and better. Applications such as waiting time estimation, traffic prediction, and parking search are good examples of how data from different sources can be used to facilitate our daily life. In this study, we consider an under-utilized data source: university ID cards. Such cards are used on many campuses to purchase food, allow access to different areas, and even take attendance in classes. In this article, we use data from our university to analyze usage of the university fitness center and build a predictor for future visit volume. The work makes several contributions: it demonstrates the richness of the data source, shows how the data can be leveraged to improve student services, discovers interesting trends and behavior, and serves as a case study illustrating the entire data science process.