This case study involves tasks that involve four crucial skills for our analyst: (1) data cleaning, (2) calculation of key performance indicators (KPIs), (3) descriptive analysis, and (4) impact evaluation.

The data sources used for this analysis include the Cyclistic trip data for 12 months between 2020 to 2021, the monthly data analyzed is from a real company called 'Divvy', shared under a Data License Agreement <https://divvy-tripdata.s3.amazonaws.com/index.html>, https://ride.divvybikes.com/data-license-agreement. The data includes the start and end time and date of each trip, the duration of the trip, the start and end station ID, the bike ID, and the user type (annual member or casual rider). The goal of this analysis is to understand how annual members and casual riders use Cyclistic bikes differently to inform marketing and operational strategies that can better meet the needs of both groups.

My Learning Jurney on Google Data Analytics with R programming using R Markdown