Uber Business Analysis

Objective​

Transform raw bookings, customers, vehicles and revenue data into actionable insights.​

Business Understanding​

Problems:​

Lost bookings, revenue tracking, rider/driver ratings.​

Goals:​

Improve booking completion rate​

Optimize revenue by vehicle type & location​

Enhance customer and driver satisfaction​

KPIs​

Revenue, completed bookings, lost bookings, distances & ratings.​

Data Preparation​

1. Data transformation from excel to power query.​

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2. Data Cleaning (Power Query):​

Check/remove duplicates​

Removing nulls​

Data format changes:​

Time: from Date and time to (time),​

Cancelled rides by customer/driver to (text “Yes and No”)​

Booking value to (whole number)​

Ride distance, driver/customer rating To (decimal number)​

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Data Modeling​

Table Types​

Dimension tables: IMG, Calendar​

Fact table: Uber​

Relationships:​

IMG (Vehicle Type) ↔ Uber (Vehicle Type) , Relationship Type: [One to Many]​

Calendar (Date) ↔ Uber (Date) , Relationship Type: [One to Many]​

​Recommendations​

Apply discounts in Feb to generate more bookings​

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Push a marketing campaign focusing on Go Sedan vehicle types​

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Optimize vehicle allocation in busy times (From 4:00PM to 10:00 PM)