This project contains a collection of SQL queries based on the Ola Rides dataset. It includes practice questions and solutions such as filtering rides, calculating average ratings, total earnings, fare per km, and identifying top drivers and customers. The project helps in understanding SQL concepts like aggregation, sorting, filtering, and joins.
📘 Overview
This project contains a collection of SQL queries based on the Ola Rides dataset. It includes various questions and their solutions that help in learning and practicing SQL for data analysis.
🎯 Objectives
Understand SQL concepts like SELECT, WHERE, GROUP BY, ORDER BY, and aggregation functions.
Perform data analysis on ride data.
Identify top-performing drivers and customers.
Calculate metrics like fare per km, fare per minute, and total earnings.
🧠 Topics Covered
Basic SQL Queries
Filtering & Sorting
Aggregation (SUM, AVG, COUNT)
Aliasing & Rounding
💾 Dataset Used
Table Name: ola.ola_rides Columns Example:
ride_id
customer_name
driver_name
fare_amount
distance_km
ride_time_min
rating
📊 Key Learnings
How to analyze ride data using SQL.
How to calculate performance metrics.
How to use aggregate functions efficiently.
🧑💻 Author
Sumit Sharma 📧 sumitkrsharma2152@gmail.com
🎓 B.Tech CSE (2022–2026), Gandhi Institute for Education and Technology Subqueries
Analytical Queries