This project analyzes OLA ride data for july 2024, using MySQL for Exploratory Data Analysis (EDA) and Power BI for creating interactive visualizations. The objective is to uncover key insights into booking patterns, cancellations, ratings, and revenue to support business decisions.
Key Insights:
- ✅ Successful Bookings: Over 12.65K rides completed.
- 🚗 Average Ride Distance by Vehicle Type: Bike had the longest rides.
- ❌ Customer Cancellations: over 2K rides.
- 👤 Top 5 Customers: Identified by booking frequency.
- 🛠 Driver Cancellations: over 3K rides
- 💸 UPI Payments: 1,284 rides paid via UPI.
- 💰 Total Successful Booking Value: ₹1,734,897.
- 🧾 Incomplete Rides: 194 due to breakdowns, customer requests, etc.
Dashboard Pages:
-
Overview
- Total Bookings
- Booking Status (Success, Cancelled)
- Ride Volume Over Time
-
Vehicle Insights
- Top 5 Vehicle Types by Distance
- Ride Distance Distribution
- Average Ratings by Vehicle Type
-
Revenue & Payments
- Revenue by Payment Method
- Top 5 Customers by Spend
-
Cancellations
- Reasons by Customer & Driver
- Cancellations by Type
-
Ratings
- Driver Rating Distribution
- Customer vs Driver Rating Comparison
Interactive Features:
- 📅 Date Slicers
- 🧮 KPIs: Total Bookings, Revenue, Cancellations, Success Rate
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This project highlights how SQL and Power BI can work together to uncover actionable insights from ride-sharing data—enabling better strategies, improved customer experience, and enhanced operational decisions.
📁 Tools Used: MySQL, Power BI
📅 Data Scope: July 2024
📌 Focus Areas: Bookings, Cancellations, Ratings, Revenue