🚕 Uber Data Analytics Dashboard

Project Overview: Developed an interactive Power BI dashboard to analyze and visualize more than 150,000 Uber ride records and generate meaningful business insights.
Business Performance Analysis: Analyzed completed, cancelled, incomplete, and lost bookings to understand overall ride performance and operational efficiency.
Revenue Analysis: Evaluated total revenue based on vehicle type, customer category, payment method, monthly trends, and quarterly performance.
Vehicle Performance: Compared different vehicle categories such as Auto, Sedan, SUV, Bike, and Prime based on bookings, revenue, and overall contribution.
Customer Analysis: Segmented riders into First-time Riders, Return Riders, and Regular Riders to understand customer behavior and preferences.
Cancellation Analysis: Identified major cancellation reasons from both customers and drivers to understand factors affecting ride completion.
Location Analysis: Analyzed pickup and drop-off locations to identify high-demand areas and busy locations.
Time-Based Analysis: Studied monthly, quarterly, and time-slot trends to identify peak demand periods and ride patterns.
Distance Analysis: Analyzed total ride distance and average distance per ride across different vehicle categories and time periods.
Payment Analysis: Compared payment preferences such as Cash, UPI, Credit/Debit Card, and Wallet across different customer segments.
Interactive Filters: Added dynamic slicers for vehicle type, date, payment method, and booking status to make the dashboard easy to explore.
Data Processing: Used Power Query, Excel, and SQL for data cleaning, transformation, and preparation before visualization.
Data Modeling: Created structured data models and used DAX measures to calculate KPIs and generate meaningful analytical metrics.
Key Insights: The dashboard helps identify revenue trends, cancellation drivers, customer patterns, vehicle performance, demand hotspots, and operational gaps.
Objective: The main goal of the project is to transform raw Uber ride data into clear, actionable insights that can support better business decisions, improve driver allocation, reduce cancellations, and enhance customer satisfaction.