2025 Data Hack Competition

Data Hack is a class where students learn about data cleaning, visualization, and descriptive analysis using R programming language. Throughout the quarter, the students learn the whole process of obtaining raw data and making it ready for analysis, therefore covering a wide variety of topics such as web scraping, merging and reshaping datasets, and even coding with AI. 

At the end of the quarter, the students have the opportunity to show the skills they learned in a competition for cash prizes. They are randomized into small groups, where they have the freedom to choose a public policy issue in California, describe it, and present the evidence in front of a panel of external judges. 

This year’s winners covered the following topics:

1st Place: Rising Rents: UC Campuses and Local Housing Markets 

Team Members: Geraldyn Gong, Ethan Lee, Agnes Poduval, Olivia Shu, Kevin Zhang 

2nd Place: Short-Term Rentals and Affordability in California 

Team Members: Cy Coldiron, Daisy Fang, Elizabeth Hung, Emily Mao 

3rd Place: High Hopes, Modest Results: The Limited Impact of California’s Minimum Wage Increase 

Team Members: Bowie Chuang, Lucas Helot, Allison Hu, Cecilia Li, Sadie Parker, Austin Zhang 

We extend our sincere thanks to Camilo Abate and Jonah Danziger for their outstanding instruction and leadership in this course. 

Special appreciation also goes to our panel of judges: David Silver, Toshio Ferrazare, and Nick Scozzaro for their time and thoughtful evaluations.