📊 Ola Performance Analytics

End-to-End Data Analytics using SQL & Power BI

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📌 Project Overview

This project analyzes Ola ride booking data to evaluate business performance, customer behavior, revenue trends, cancellations, and service quality.
The solution uses SQL for data modeling & analysis and Power BI for interactive dashboards, enabling data-driven operational decisions.

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🎯 Business Objectives

• Analyze total bookings and successful rides
• Identify revenue drivers and high-value customers
• Understand cancellation reasons
• Evaluate customer & driver satisfaction
• Compare performance across vehicle types

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🧹 Data Preparation

• Cleaned and standardized booking data
• Handled missing and inconsistent values
• Created analytical fields such as:
  • Booking status categories
  • Vehicle-wise metrics
  • Rating summaries
• Loaded transformed data into MySQL for analysis

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🧮 SQL Analysis

SQL queries and views were created to answer key business questions:

• Successful vs canceled bookings
• Average ride distance by vehicle type
• Revenue by payment method
• Top 5 customers by booking value
• Driver & customer cancellation reasons
• Rating analysis by service type

📂 SQL scripts available here:
👉 `ola.sql'

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📊 Power BI Dashboards

🧭 1. Overall Dashboard

Purpose: High-level overview of Ola’s operational performance.

Key Metrics:

• Total Bookings: 103,024

• Successful Bookings: 63,967

• Cancelled Bookings: 28,933

• Cancellation Rate: 28.08%

• Total Booking Value: 35M

Visual Insights:

📈 Ride Volume Over Time: Shows daily booking fluctuations and demand patterns

🥧 Booking Status Breakdown:

Success:

• Cancelled by Customer

• Cancelled by Driver

KPIs:

• Total Bookings
• Successful Bookings
• Total Booking Value
• Cancellation Rate

🔗 Dashboard Image:
👉 View Overall Dashboard

Business Insight: A cancellation rate of ~28% highlights a significant opportunity to improve customer experience and operational efficiency.

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🚗 2. Vehicle Type Dashboard

Purpose: Compare performance across vehicle categories.

Metrics by Vehicle Type:

• Total Booking Value:

  -- Prime Sedan: ~8.30M

  -- Prime SUV: ~7.93M

  -- Prime Plus: ~8.05M

  -- Mini: ~7.99M

  -- Auto: ~8.09M

  -- Bike / E-Bike: ~8.18M

• Successful Booking Value: Ranges between 4.88M – 5.22M

• Average Distance Travelled:

  -- Prime vehicles: ~25 km

  -- Auto & Bike: ~10–25 km

Business Insight: Premium vehicle categories generate higher revenue, while Autos and Bikes handle shorter, high-frequency trips.

🔗 Dashboard Image:
👉 View Vehicle Type Dashboard

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💰 3. Revenue Dashboard

Purpose: Analyze revenue sources and customer contribution.

Key Metrics:

• Total Revenue: 35M

• Top 5 Customers Contribution: ~3.26M combined

• Highest Revenue Payment Method: Cash

• Second Highest: UPI Insights:

• Revenue by payment method (Cash, UPI, Cards)

• Daily revenue trend

• Top 5 customers by booking value

🔗 Dashboard Image:
👉 View Revenue Dashboard

Business Insight: Cash and UPI dominate transactions, while a small customer segment contributes a disproportionately high share of revenue.

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❌ 4. Cancellation Dashboard

Purpose: Identify reasons behind ride cancellations.

Key Metrics:

• Total Bookings: 103,024

• Cancelled Bookings: 28,933

• Successful Bookings: 63,967

• Cancellation Rate: 28.08%

KPIs:

• Total Bookings
• Successful Bookings
• Canceled Bookings
• Cancellation Rate (~28%)

Breakdown:

• Customer cancellations (change of plans, delays, issues)
• Driver cancellations (personal & vehicle-related issues)

🔗 Dashboard Image:
👉 View Cancellation Dashboard

Business Insight:

• Customer-initiated cancellations are higher than driver cancellations, indicating scope for improving wait times and service reliability.

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⭐ 5. Ratings Dashboard

Purpose: Measure service quality and customer satisfaction.

Metrics:

• Average Customer Rating: ~4.00

• Average Driver Rating: ~4.00

Ratings by Vehicle Type:

• Prime Sedan: ~4.00

• Prime SUV: ~4.01

• Prime Plus: ~4.00

• Mini / Auto / Bike: ~3.98 – 4.00

🔗 Dashboard Image:
👉 View Ratings Dashboard

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🔍 Key Business Insights

• ~28% cancellation rate indicates scope for operational improvement
• Premium vehicle categories generate higher revenue
• Cash & UPI dominate payment methods
• Customer and driver ratings are stable around 4.0

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🧰 Tech Stack

Category	Tools
Language	SQL
Database	MySQL
BI Tool	Power BI
Data Prep	Excel
Version Control	Git, GitHub

📂 Project Structur

── data/ ├── sql_queries/ │ └── ola.sql ├── dashboards/ │ ├── overall_dashboard.png │ ├── vehicle_type_dashboard.png │ ├── revenue_dashboard.png │ ├── cancellation_dashboard.png │ └── ratings_dashboard.png └── README.md

👤 Author

Prince
📧 Email: raushanmahto999@gmail.com
🔗 GitHub: https://github.com/mahtoraushan999
🔗 LinkedIn: https://www.linkedin.com/in/raushan-kumar-6a1171382