Introduction: Cyclistic 2021

This case study is based off of a framework for one of the  examples used in the Capstone Project for Coursera’s Google Data Analytics Certificate Course. It details a scenario where we, the students, are to pretend that we are a junior analyst at a Company called Cyclistic. This is a made-up company, but the data used is from a real bike-sharing and urban service company called Motivate International Inc. Using the publicly released data of one of Motivate International’s bike-sharing  service areas, we can act as if this is the data collected by our fictional company, Cyclistic. 

In this scenario, the director of marketing at Cyclistic believes that converting more of their casual riders into members with annual subscriptions will increase company profits. We are tasked with conducting an analysis to determine how casual riders use the service differently from annual members. After making a report on our findings,  we are to offer 3 recommendations as to how we can get more riders to sign on for an annual membership.

The Coursera course offers this and one more scenario for us to use as our capstone project, and also allows us to conduct an analysis on whatever subject we choose. For the two scenarios given to us, we are shown a step-by-step route from which to conduct our analysis and make a report. I chose to follow a more free-form route for this analysis, using my own process to find results and offer insights. In the future, I may post a second analysis for this scenario where I follow the framework laid out by the course . 

Our analysis will be structured using the 6 Steps of Data Analysis taught in the course: Ask, Prepare, Process, Analyze, Share, and Act. Throughout all of this process, we will be using various analysis tools to complete our project. These tools include Microsoft SQL Server, R programming language, Microsoft Excel, and the Mito tool in Python’s Anaconda.

We will begin our analysis with the first step: the “Ask” Phase.