📊 OLA Data Analyst Project
An end-to-end Data Analytics project covering SQL, Power BI, and Data Storytelling to analyze OLA ride trends, customer behavior, cancellations, revenue patterns, and performance metrics.
🔥 Project Overview
This project analyzes one month of OLA ride data containing 100,000+ records. It aims to uncover insights related to:
Ride volume patterns
Booking status and cancellation behavior
Revenue distribution
Customer & driver ratings
Vehicle type performance
Top customers and booking trends
🛠 Tech Stack Used SQL
Data Cleaning
KPI Calculations
Trend Analysis
Aggregations using GROUP BY, Views, Functions
Power BI
Data Modelling
DAX Measures
Dashboard creation
Trend charts, KPI cards, distribution visuals
📌 Business Questions Answered (SQL) ✔ 1. Retrieve all successful bookings ✔ 2. Average ride distance by vehicle type ✔ 3. Total cancelled rides by customers ✔ 4. Top 5 customers with maximum bookings ✔ 5. Driver cancellation due to personal/car issues ✔ 6. Max/Min driver ratings for Prime Sedan ✔ 7. Rides paid using UPI ✔ 8. Average customer rating per vehicle type ✔ 9. Total booking value of successful rides ✔ 10. Incomplete ride reasons
(Queries available in SQL file)
📊 Power BI Dashboard Insights
Dashboard Includes:
Ride volume over time
Booking status breakdown
Cancelled ride reasons (Customer vs Driver)
Revenue by payment method
Top customers by booking value
Ratings distribution
Ride distance distribution per day
🔍 Key Insights
Customer cancellations mostly due to drivers not moving toward pickup
Weekend rides have higher order value & frequency
Prime Sedan generates the highest average rating
UPI is the most preferred payment method
Top 5% customers contribute more than 35% of revenue
🏁 Conclusion
This project demonstrates skills in: ✔ SQL (Joins, Aggregations, Views) ✔ Data modeling in Power BI ✔ Analytical thinking ✔ KPI-driven storytelling
A perfect resume-ready Data Analyst Portfolio Project.
This dashboard provides a high-level summary of total bookings, successful rides, revenue, booking status breakdown, and ride volume over time.
This dashboard compares vehicle types based on booking value, successful bookings, average distance traveled, and total distance covered.
This dashboard highlights revenue distribution by payment method and top customers by total booking value.
This dashboard shows ride cancellations by customers and drivers along with detailed cancellation reasons.
This dashboard analyzes customer and driver ratings across different vehicle types to measure service quality.
👤 Author
Sunil Kumar Data Analyst Aspirant | SQL | Power BI | Excel | Python