This case study is the capstone project for my Google Data Analytics Professional Certificate. The goal is to analyze the historical trip data of Cyclistic, a fictional bike-share company in Chicago, to understand how Annual Members and Casual Riders use the service differently. By analyzing a dataset of over 700,000 records, I aim to identify trends that will inform a new marketing strategy focused on converting casual riders into long-term annual members. Key Technical Steps: - Data Processing: Combining multiple datasets and ensuring consistency. - Data Cleaning: Using R to handle missing values, recode variables, and filter out dirty data (e.g., negative trip durations). - Exploratory Data Analysis (EDA): Aggregating data to compare trip durations and frequency across different days of the week. - Visualization: Creating clear, high-impact charts using ggplot2 to present findings to stakeholders.