This was my Capstone Project for the Google Data Analytics Certificate. It utilized MySQL to analyze 5.5 million bike-share records and used Microsoft Excel to build a data visualization dashboard.
Business Case | Data Description | Approach | Results | In-Depth Analysis | Credits
This is the more in-depth longer version of the process
Ask | Prepare | Process | Analyze | Share | Further Considerations
What is the problem you are trying to resolve?
How can your insights drive business decisions?
Where is your data located?
How is the data organized?
Are there issues with bias or credibility in this data? Does your data ROCCC?
How are you addressing licensing, privacy, security, and accessibility?
How did you verify the data's integrity?
How does it help you answer the question?
Are there any problems with the data?
What tools are you using and why?
Have you ensured your data's integrity?
What steps have you taken to ensure your data is clean?
How can you verify that your data is clean and ready to analyze?
Have you documented your cleaning process so you can review and share those results?
How should you organize your data to perform an analysis on it?
Has your data been properly formatted?
What surprises did you discover in your data?
What trends or relationships did you find in your data?
How will these insights help answer your business questions?
Were you able to answer the question of how annual members and casual riders use Cyclistic bikes differently?
What story does your data tell?
How do your findings relate to your original question?
Who is your audience? What is the best way to communicate with them?
Can data visualization help you share your findings?
Is your presentation accessible to your audience?
What is your final conclusion based on your analysis?
How could your team and business apply your insights?
What next steps would you or your stakeholders take based on your findings?
Is there additional data you could use to expand your findings?