🎬 Movie Ticket Booking Analytics

This project simulates a real-world movie ticket booking system. It demonstrates data modeling, cleaning, and advanced SQL analytics to uncover meaningful business insights demonstrating end-to-end data analysis, from raw data to actionable insights — all structured for clarity and collaboration.

📌 Key Features

• Well-structured database schema representing customers, movies, shows, theatres, accounts, and tickets.

• Data cleaning techniques (string manipulation, conversions, type casting).

• SQL practice with filtering, aggregation, joins, window functions, and CTEs.

• Business-oriented use cases like customer value analysis and city-level performance.

🗂️ Project Structure

movie-ticket-booking-analytics/

• data - Raw or sample data files

• schema - Database schema documentation (ERD, DDLs)

• cleaning_scripts - SQL cleaning/update scripts

• queries - All practice queries and use-case queries

• screenshots - Screenshots of sample data or results

• README.md - Project overview

🚀 Technologies

• MySQL
• VS Code / MySQL Workbench
• Git & GitHub

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📈 Goals

• Showcase SQL skills with real-life inspired use cases.
• Build a complete analytics-ready database from raw structured data.
• Present work cleanly for recruiters and hiring managers.

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🔥 Highlights

• Used JOIN, GROUP BY, HAVING, LIMIT, OFFSET, RANK, CTE, etc.
• Cleaned duration formats, derived new columns (total seats, payment method).
• Summarized customer and city-level performance using advanced queries.

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📬 Connect

If you're a recruiter or someone curious about this project, feel free to reach out!

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