This project is the capstone project for the Google Business Intelligence Professional Certificate on Coursera.
Project Overview
Cyclistic is a fictional bike-share company in New York City. There are bike stations located throughout 5 boroughs and customers can rent bikes for easy travel between stations at these locations. This project seeks to identify customer demand at different station locations and provide insights into how customers are using their bikes.
Project goal: inform new station growth and increase customer base.
Business Problem
The Customer Growth team needs visibility into customer demand among different user types (subscribers and non-subscribers) and across different locations in New York.
- Primary data - NYC Citi Bike Trips
- Secondary data - Census Bureau US Boundaries, NOAA GSOD Weather, location match (zip code - neighborhood).
Deliverables: dashboards that summarize key metrics and insights
Technical Solution
To provide the team with both business value and organizational data maturity:
- I used SQL coding to design an ETL data pipeline on Google Cloud Platform (GCP) that extracts data from 4 different sources, aggregated metrics, and loaded the transformed data to target destinations.
- I then leveraged the ETL pipeline to automate data updates for dashboard design in Tableau.
- I designed dashboards to lend insights into station congestion, bike routes, peak time, and weather impact on customer usage (subscribers & non-subscribers).
Data Sources
Bike trips data
Census Bureau US Boundaries
National Ocean and Atmospheric
Administration
Data Store & Transformation
Visualization Tool
Business Users
Key to success:
- The dashboards are user-friendly and summarize insights at aggregate level with multiple filters to serve various business users’ interests.
- The dashboards eliminate manual, repetitive analysis efforts as they automatically update with newest daily data available and readily refresh for end users.
Business Impact
The dashboards feature several filters to focus on user type, time period, starting/ending neighborhood and borough areas while providing visibility into customer demand and bike route details. Customer Growth team, and other interest stakeholders, can access bike usage data in the last one-year period.