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This project showcases a complete data analytics workflow using a dataset created with AI. SQL was used for data cleaning and preparation, followed by analysis in Excel. For visualization, the dataset was connected through Google Sheets and presented in interactive Power BI dashboards.

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πŸš– Ride Booking Data Analyst Project

Welcome to the OLA Data Analyst Project! This project demonstrates a complete data analytics workflow, covering data extraction with SQL, analysis with Excel, and visualization using Power BI. The dataset was AI-generated and connected to Power BI through Google Sheets for real-time updates. πŸ“Šβœ¨

πŸ“‹ Project Overview

πŸ” Tools & Technologies:

  • πŸ—„οΈ SQL for Data Extraction and Preparation: Writing queries to clean, filter, and aggregate data for insights.
  • πŸ› οΈ Google Sheets: Data hosting for Power BI integration and for Data Analysis.
  • πŸ“Š Power BI for Visualization: Creating interactive dashboards to communicate findings effectively
  • πŸ€– AI: Dataset generated with AI, connected to Power BI via Google Sheets.

πŸ”‘ Key Insights

  • πŸ’Έ Revenue: Total bookings generated $57M, while cancellations caused a $21M loss.
  • πŸ›‘ Cancellations: The majority of driver cancellations were due to personal or vehicle issues.
  • 🌟 Ratings: Both customers and drivers averaged a rating of 4.0.
  • πŸš— Vehicle Performance: Prime Sedan and Auto were the most profitable vehicle types.

πŸ“Š Power BI Dashboard

Here’s a preview of the Power BI dashboard used in this project:

1. Overall Analysis πŸ“‹: Total bookings, revenue trends, and cancellation patterns.

2. Vehicle Analysis πŸš—: Popular vehicles, average ride distances, and vehicle-specific ratings.

3. Revenue Analysis πŸ’Έ: Revenue trends by location, time, and vehicle type.

4. Cancellation Analysis πŸ›‘: Reasons for cancellations by customers and drivers.

5. Ratings Analysis 🌟: Distribution and trends in customer and driver ratings.

πŸ“œ How to Use This Project

1. Clone the repository:

git clone https://github.com/theDhanendra/Ride_Bookings.git

2. Navigate to the project folder:

cd Ride_Bookings

3. SQL:

  • Open "ola_analysis.sql" in any SQL editor (e.g., MySQL Workbench).
  • Execute queries for data extraction and insights.

4. Power BI:

  • Open "ola_dashboard.pbix" in Power BI Desktop to explore the dashboard.

5. Optional:

  • View Ola_Dashboard.pdf for a summary of key visualizations.

🀝 Contributing

Contributions are welcome! Fork this repository and submit a pull request with your enhancements. Let's build something amazing together. 🌟

πŸ“ž Contact

For queries or feedback, reach out at:

About

This project showcases a complete data analytics workflow using a dataset created with AI. SQL was used for data cleaning and preparation, followed by analysis in Excel. For visualization, the dataset was connected through Google Sheets and presented in interactive Power BI dashboards.

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