M1 EDA Hackathon

Team of corgis winning a hackathon. 2022. Roman x Stable Diffusion

In this hackathon, you will be using everything you have learned so far (and some things still coming up next week) to create a striking and informative dashboard. The winning group will receive an even more amazing prize!

What to do?

In groups, find an exciting dataset of similar complexity as the ones we worked with in class (e.g. comparable to Open Policing, Airbnb). You can find them, for instance, on Kaggle.

Consider also:

Steps for the analysis

  • Perform EDA and answer interesting questions about the data. You can use geospatial analysis (if you like). You do not have to scrape or generate data, but you can. Perform analyses first in a notebook and generate all relevant calculations and plots there.
  • On Sept. 13th, we’ll introduce you to Streamlit, a framework for webapp development. You are obviously welcome to look into it on your own before that.
  • The submission deadline will be on the 15th (noon) - as a deployed (accessible online) web app. You will pitch your dashboard in class. We will forward all submitted apps to an expert jury for evaluation.

The winning team will be announced in the week between 19. and 23. September. 🎉

The Jury

Mathias Boe Flinta CTO at Scandinavian Medical Solutions

Mathias is Head of Data & Analytics & IT at SMS (Scandinavian Medical Solutions). He finished his studies in cand.oecon. (MSc. Economics) one year ago, during which he specialized in BI and Data Science. Currently, he is implementing a new ERP system, which will set a good foundation for BI analysis and predictive foresting with Data Science within the coming year.

Karolina Grodzinska Data Analyst Co-op @ Schneider Electric, Boston US

Karolina currently works as a data analyst at Schneider Electric. She’s also been chosen as a Tableau Student Ambassador for the upcoming academic year. In her free time, she likes to participate in data visualization challenges.

David Jan Lazar Data Scientist at DataSentics, an Atos Company.

David has completed a Social Data Science semester at Aalborg University and a Masters Degree from Business Intelligence at Aarhus University. He works as a data scientist at DataSentics, a consulting firm that provides business solutions based on machine learning in areas of business, finance, insurance, natural language processing, computer vision and more.