This repository contains my capstone project completed as part of the Google Data Analytics Professional Certificate on Coursera. The project applies the full data analysis process—Ask, Prepare, Process, Analyze, Share, and Act—using real-world data to derive business insights and inform decision-making.
The analysis is based on a fictional dataset provided by Cyclistic, a bike-share company in Chicago. The goal of this project is to help the marketing team design strategies that convert casual riders into annual members.
How do annual members and casual riders use Cyclistic bikes differently?
By exploring usage trends and customer behaviors, this project aims to provide actionable recommendations to increase user retention and membership conversion.
Excel for initial data cleaning R (Tidyverse, ggplot2) for data wrangling and visualization SQL for querying structured datasets Tableau for creating interactive dashboards
Casual riders are more active on weekends, while annual members ride more during weekdays Annual members have shorter average ride durations, suggesting more frequent, utilitarian usage Popular ride types and stations vary significantly between the two user segments
Offer weekend membership promotions targeted at casual riders Highlight convenience and cost savings of annual plans in marketing materials Place membership offers at high-traffic casual rider stations