Business+Tech Data Download and Datathon Competition Group

2026 Business+Tech Datathon and Data Download

UNCOVER INSIGHTS AND UNLEASH INNOVATION WITH DATA ANALYTICS.

Comprehending large data sets, evaluating data with a critical eye, and utilizing data to make informed decisions are ALL skills that are essential to thrive in the tech industry. Every winter, Business+Tech hosts the Data Download and Datathon Competition, in partnership with tech consulting firms Deloitte and PwC, for participants to practice analyzing a real-world problem.

Datathon Competition | February 1 – February 6, 2026

During this virtual and in-person week-long hackathon style competition, interdisciplinary student teams use data as the primary basis for developing creative solutions to a real-world problem. Once the problem statement and data set are released at the kickoff, teams of 5-6 students have a week to analyze, propose, and persuade a panel of judges.                         

Data Download | January 26 – January 28, 2026

3 workshops geared toward advancing your data analytics skills through a +tech lens. These sessions help prepare students to excel in the Datathon Competition and win the $3,000 grand prize. Session topics include: PowerExcel, Data Cleaning with R, and Python & AI

Comprehending large data sets, evaluating data with a critical eye, and utilizing data to make informed decisions are ALL skills that are essential to thrive in the tech industry. Every January, Business+Tech hosts the Data Download and Datathon Competition, in partnership with tech consulting firms Deloitte and PwC, for participants to practice analyzing a real-world problem.



-
Ross School of Business, R1240
Livestream Available (Visible After Registration)
To Be Announced

Utilizing large and complex datasets allows organizations and individuals to make more informed decisions with higher accuracy. But parsing through messy or incomplete data can be incredibly difficult. Join Dr. Hanan Swidan for this Data Cleaning with R workshop to learn how to uncover and uncomplicate complex datasets to create conditions for more accurate and reliable analytics results. 


*This event is hybrid and has a virtual option for online/remote students. 

For questions or contact information click here