Welcome to the Cyclistic bike-share analysis case study! In this case study, I have perform many real-world tasks of a junior data analyst. For this case study, I will work for a fictional company called, Cyclistic. I will meet different characters and team members. In order to answer the key business questions, I will follow the steps of the data analysis process: Ask, Prepare, Process, Analyze, Share and Act.

Scenario: I'm a junior data analyst working in the marketing analyst team at Cyclistic, a bike-share company in Chicago. The director of marketing believes the company’s future success depends on maximizing the number of annual memberships. Therefore, my team wants to understand how casual riders and annual members use Cyclistic bikes differently. From these insights, my team will design a new marketing strategy to convert casual riders into annual members.

But first, Cyclistic executives must approve my recommendations, so they must be backed up with compelling data insights and professional data visualizations.

Collecting data and License:

The datasets have a different name because Cyclistic is a fictional company. For the purposes of this case study, the datasets are appropriate and will enable me to answer the business questions. The data has been made available by Motivate International Inc.

under this link: https://ride.divvybikes.com/data-license-agreement

The data I'm using was provided to me through the case study road map for the Coursera: Google Data Analytics Professional Certificate.

Under this link: https://divvy-tripdata.s3.amazonaws.com/index.html

This is public data that you can use to explore how different customer types are using Cyclistic bikes. But note that data-privacy issues prohibit you from using riders’ personally identifiable information. This means that you won’t be able to connect pass purchases to credit card numbers to determine if casual riders live in the Cyclistic service area or if they have purchased multiple single passes