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🌟 Divvy Bike Dataset Case Study - Insights & Recommendations 🚴♂️ In-depth analysis of the Divvy Bike dataset, exploring over 5.6 million bike trips recorded in 2023 in Chicago! Learn how casual riders and members differ, key trends in bike usage, and actionable strategies to boost membership for long-term success. 🎯 Key Topics Covered: 🚲 Overview of Divvy Bike types and member categories. 📊 Insights into bike usage patterns by month, season, and day of the week. 🛠️ Data cleaning challenges and solutions using SQL. 💡 Recommendations for marketing strategies to convert casual riders into annual members. Discover how data can drive real-world business decisions. Gain insights into how external factors like seasons and ride duration impact customer behavior. Learn practical tips for implementing membership campaigns. 📌 Presented by Shan Aziz A passionate data analyst ready to transform insights into impact. 🌐 Website: https://shanaziz.carrd.co/ Email: [email protected] LinkedIn: / shanaziz GitHub: https://github.com/shan-aziz/Divvy-Bi... References: https://divvybikes.com/system-data Data Source: https://divvy-tripdata.s3.amazonaws.c... Divvy & City of Chicago. (2023). Divvy Bike Dataset. City of Chicago. (2023). Open Data Portal. This portal provides access to a variety of datasets, including those related to the Divvy bike-sharing program. National Association of City Transportation Officials (NACTO). (2023). Bike Share in the U.S.: 2023. This report provides insights into bike-sharing trends and statistics across major U.S. cities. DeMaio, P. (2009). Bike-sharing: History, Impacts, Models of Provision, and Future. Journal of Public Transportation, 12(4), 41-56. This article discusses the evolution and impact of bike-sharing systems. Fishman, E. (2016). Bikeshare: A Review of Recent Literature. Transport Reviews, 36(1), 92-113. This literature review offers a comprehensive overview of research related to bike-sharing systems.