This project was an individual project I made by myself to practice my skills, especially in querying and exploring the data directly from the database system (Google BigQuery). I also practiced creating advanced charts such as the Sankey diagram and destination maps in Tableau.

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Background information

Bike share is a convenient, healthy, affordable, and fun form of transportation. It involves a fleet of specially designed bikes locked into a network of docking stations. The bikes can be unlocked from one station and returned to any other station in the system.

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Objective

I wanted to know what happened to the business in 2015 and what was the busiest station at that time.

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Analysis Method

I queried information using SQL from Google BigQuery: 

• trip id

• date of the trip

• duration of the trip

• arrival and departure bike station (including the geographical location)

• user type (subscriber or regular)

Then, I transformed the information into an insightful dashboard below.

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Insights

As shown in the dashboard below, we got information here.​​

• There's a slight increase of 6% YoY on total trips in 2015.

• San Francisco had 55 bike stations in 2015.

• The users (84.3% of total trips) tend to have short to medium trips (0-15 minutes). The average is around 8.92 minutes per trip.

• The subscribers (1-month or 1-year membership) did 87.1% of the total trips, while the regular user (1-day or 3-day membership) only contributed 12.9%. 

• The subscribers tend to have a trip under 30 minutes (they rarely take a very long trip). Meanwhile, the regular users tend to have over 7.5 minutes trips (they rarely take a short trip). 

• Lyon St at Fell St became the busiest bike station in 2015.

  • The highest total trips that departed at Lyon St at Fell St were from 2nd St at Townsend St (2145 trips)

  • The highest total trips that arrived at Lyon St at Fell St were from Parker Ave at McAllister St (2608 trips) ​