Divvy Bikes Dashboard

The Project was to look at how customers are using Divvy Bikes across all stations. The data was extracted from online and it was only for 1 year (2019), data was in Quaters(1-4) so the data was imported into excel for cleaning. In excel I noticed the Quater 2 data has a different header compared to other Quaters so it was rename to make it easier to combine together, a new column was added to calculate the Ride_lenght in HH:MM:SS, a coloumn was also created to show the Day_of_week. Then the data was imported into SQL where some descriptive statistics (Average ride_lenght, Total no. of bikes, Count of distinct station ID for "To" and "from" was done, then fuction "UNION" was used to combine the tables together into one single table. Power BI was used for the Data visulisation the SQL database was connected to Power BI and a date table was created just so we can drill down into the data.
From the analysis Here are my FIndings:

• Annual Members (Customers) take more long trip than Subscribers
• Annual Members (Customers) take more ride during weekends while Subscribers take more ride suring weekdays
• There is an increase in the use of Divvy Bike during (April - November)

The following are ways Divvy Bike can improve the Business next year:

• Advertise and give discount for Casual member to become a subscriber
• Share the benefits of being a subscriber to Casual riders and if possible share bike usage report with them
• More subscription based activities should be done during the weekends within April to November