This project marks the beginning of my data analysis journey - a time when I was so new to the field that I didn’t even know about markdown or Jupyter notebooks. Instead, I was pasting code and outputs directly into a PDF document!

As part of the Google Data Analytics Certification capstone, I analyzed data from Cyclistic, a fictional bike-share company in Chicago. The goal was to understand how annual members and casual riders use Cyclistic bikes differently, and to provide insights that could help convert casual riders into annual members.

Key Components

• Data Source: 12 months of Cyclistic trip data (2022)
• Tools Used: Google Sheets, BigQuery SQL, R, Tableau
• Analysis Process: Followed the data analysis steps of Ask, Prepare, Process, Analyze, Share, and Act

What I Did

1. Cleaned and prepared data using Google Sheets and BigQuery SQL
2. Performed exploratory data analysis using SQL queries
3. Created visualizations with R and Tableau to uncover usage patterns
4. Analyzed differences between annual members and casual riders in terms of ride frequency, duration, and popular stations
5. Provided data-driven recommendations for converting casual riders to annual members

Key Findings

• Annual members took nearly twice as many rides as casual riders
• Casual riders had longer average ride durations
• Weekday vs. weekend usage patterns differed between the two groups
• Certain stations were more popular among casual riders

Conclusion

This project not only helped me apply the skills I learned during the Google Data Analytics Certification but also sparked my passion for data analysis. It represents the starting point of my data journey, showcasing my ability to derive insights from raw data and present actionable recommendations.