Resources
Guides
Getting Started with DataFest
New to data analysis competitions? Here are some resources to help you prepare:
Recommended tools:
R, Python, Tableau, Excel, or any data analysis software you are comfortable with
Team collaboration:
Consider using shared documents, version control (Git), or cloud storage to coordinate your work
Time management:
Plan to spend time on data cleaning, exploratory analysis, focused investigation, and presentation creation
Analysis Support
What Makes a Strong DataFest Project?
Successful teams typically:
- ✓Start with exploratory data analysis to understand the structure and quality of the data
- ✓Formulate a clear, interesting research question
- ✓Use appropriate statistical or computational methods
- ✓Create clear, informative visualizations
- ✓Tell a compelling story that connects data insights to real-world implications
Common Pitfalls to Avoid
- ⚠Spending too much time cleaning data and not enough time on analysis
- ⚠Trying to answer too many questions instead of going deep on one or two
- ⚠Creating overly complex models when simpler approaches would suffice
- ⚠Neglecting to check assumptions or validate findings
- ⚠Leaving presentation creation until the last minute