In this data analyst project, I was asked to analyze the Cyclistic three years of bike trip data to identify trends. Then, I need to give a recommendation to Cyclistic executive team to increase membership.
Tools used: R for data cleaning and Tableau for data visualization
My team wants to understand how casual riders and annual members use Cyclistic bikes differently to convert casual riders to annual members
The data has been made available by Motivate International Inc. under this license.) 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.
:- Create reports and data visualizations to guide decision-making across the team
- Clean the data using R programming
- Tableau
- R
dplyr
tidyr
ggplot2
lubridate- Bike users
- Demographic
- Sales/Revenue
