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## Event details

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**When:** Friday, March 20 at 5:00pm - Sunday, March 22 at 5:00pm

**Where:** Perkins Library, Duke University


ASA DataFest<sup><small>TM</small></sup> begins with a Friday welcome where you’ll be introduced to a
surprise, real-world dataset and the organization behind it. Over the
weekend, teams will explore the data, develop a research question, and
conduct their own analysis.

Projects are due Sunday afternoon. Teams will present their findings to
a panel of faculty and industry judges, with prizes awarded for
categories such as best visualization, best use of external data, and
best overall insights.
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## What is DataFest?

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[Click
here](https://stat.duke.edu/news/students-put-classroom-skills-practice-duke-datafest-2024)
to read a news article published in Duke Daily about the 2024 winners!
[Click here](https://www.youtube.com/watch?v=5oG0UAHRWOk) to watch a
highlight video from a previous DataFest!
:::

ASA DataFest<sup><small>TM</small></sup> is a data analysis competition
where teams of up to five students attack a large, complex, and surprise
data set over a weekend. Your job is to represent your school by finding
and communicating insights into these data. The teams that impress the
judges will win prizes as well as glory for their school. Everyone will
have a great experience, lots of food, and fun!

ASA DataFest<sup><small>TM</small></sup> is also a great opportunity to
gain experience that employers are looking for. Having worked on a data
analysis problem at this scale will certainly help make you a good
candidate for any position that involves analysis and critical thinking,
and it will provide a concrete example to demonstrate your experience
during interviews.

ASA DataFest<sup><small>TM</small></sup> at Duke is organized by the
Department of Statistical Science and the Statistical Science Majors
Union (SSMU) at Duke University.

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## Sponsors

<a href="sponsors.html" class="sponsors-image-link">
<img src="logos/sponsors2026.png" alt="DataFest Sponsors" class="sponsors-full-image" loading="lazy"/>
</a>
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