- Formulate questions
- Find data. Use the techniques we have seen during the course
- Transform the data
- Load it into SQL
- Generate a
queries.sqlfile with all the descriptive queries you think may add value to your project - Visualize: you can do this through python libraries for the exploratory part
- Use Machine learning #optional
- Create a Tableau dashboard
- Create a compelling presentation sharing the insights you found
Every project should have: EDA, ETL (using SQL) and Tableau visualization.
- Create an issue on this repo and comment with the link to your github project. Please remember to keep it public and update the link if you ever decide to change its name. Make it easier for other ironhackers to start their project!
Make sure you follow this structure
data/
images/
src/
1-module-that-does-things.py #but change the names and make it meaningful. Do NOT call python files `functions.py`
2-module-that-does-things.py
3-module-that-does-things.py
queries.sql
main.py
.gitignore
requirements.txt
env.yml
presentation.pptx #Only if you decided to create one
- Make sure it is complete enough
- If you have images, add them
- Embed your shareable Tableau public link into it
- DO include a gif (by recording your screen) of a demo of your project. Do this for two reasons:
- To get the viewer's attention
- Because things fail, so this will be a back-up plan to showcase your work
- There's no
.envfile uploaded - You don't have any temporary files: .DS_Store, .ipynb_checkpoints,
__pycache__, etc - You have meaningful names in your files
- Your code is commented (#) and documented (docstrings)
- Commit often! You certainly do not want to lose weeks worth of work. Trust us, it has happens more than you think!