🚖 OLA Ride SQL Data Analysis 📌 Project Overview
This project analyzes OLA ride booking data using SQL to extract useful insights related to bookings, customers, vehicles, cancellations, ratings, and revenue.
The project contains SQL queries designed to answer real-world business questions using a ride-booking dataset.
🛠️ Technologies Used PostgreSQL SQL CSV Dataset pgAdmin / PostgreSQL environment 📂 Dataset
The project uses an OLA ride dataset containing ride and booking-related information.
Key fields used in the analysis include:
Booking ID Customer ID Booking Status Vehicle Type Ride Distance Booking Value Driver Ratings Customer Rating Cancellation Reasons Incomplete Ride Information 📊 SQL Analysis Performed
- Retrieve Successful Bookings
Identified all rides where the booking status was Success.
SELECT * FROM ride_data WHERE booking_status = 'Success'; 2. Average Ride Distance by Vehicle Type
Calculated the average ride distance for each vehicle type.
SELECT Vehicle_Type, ROUND(AVG(Ride_Distance)::numeric, 2) AS Avg_Distance FROM ride_data GROUP BY Vehicle_Type; 3. Customer-Cancelled Rides
Calculated the total number of rides cancelled by customers.
SELECT COUNT(*) FROM ride_data WHERE Booking_Status = 'Cancelled by Customer'; 4. Top 5 Customers by Number of Rides
Identified the five customers who booked the highest number of rides.
SELECT Customer_ID, COUNT(Booking_ID) AS Total_Rides FROM ride_data GROUP BY Customer_ID ORDER BY Total_Rides DESC LIMIT 5; 5. Driver Cancellations
Calculated rides cancelled by drivers because of personal and car-related issues.
SELECT COUNT(*) FROM ride_data WHERE Reason_for_Cancelling_by_Driver = 'Personal & Car related issues'; 6. Driver Ratings for Prime Sedan
Found the maximum and minimum driver ratings for Prime Sedan bookings.
SELECT MAX(Driver_Ratings) AS Max_Rating, MIN(Driver_Ratings) AS Min_Rating FROM ride_data WHERE Vehicle_Type = 'Prime Sedan' AND Driver_Ratings IS NOT NULL; 7. Average Customer Rating by Vehicle Type
Calculated average customer ratings for each vehicle type.
SELECT Vehicle_Type, ROUND(AVG(Customer_Rating)::numeric, 2) AS Avg_Customer_Rating FROM ride_data WHERE Customer_Rating IS NOT NULL GROUP BY Vehicle_Type; 8. Total Booking Value
Calculated the total booking value of successfully completed rides.
SELECT ROUND(SUM(Booking_Value)::numeric, 2) AS Total_Booking_Value FROM ride_data WHERE Booking_Status = 'Success'; 9. Incomplete Rides
Retrieved incomplete rides along with their reasons.
SELECT Booking_ID, Incomplete_Rides_Reason FROM ride_data WHERE Incomplete_Rides = '1';
The project source contains these booking, distance, cancellation, customer, rating, booking-value, and incomplete-ride analyses.
🧠 SQL Concepts Used SELECT WHERE GROUP BY ORDER BY LIMIT COUNT() SUM() AVG() MAX() MIN() ROUND() NULL handling Filtering Aggregation Business-oriented SQL analysis 📁 Project Structure Ola-Ride-SQL-Analysis/ │ ├── README.md │ ├── sql/ │ └── ola_ride_analysis.sql │ ├── data/ │ └── ola_ride.csv │ └── docs/ ├── Ola_Ride_SQL_Project.pdf ├── Ola_Ride_SQL_Project.pptx └── Ola_Ride_SQL_Questions.docx 🎯 Key Skills Demonstrated SQL Query Development PostgreSQL Data Analysis Data Filtering Aggregation Customer Analysis Ride Analysis Vehicle Analysis Cancellation Analysis Rating Analysis Business Problem Solving