🎵 Music Store Analysis with SQL

This project is an end-to-end SQL case study using a music store database. The goal is to analyze customer behavior, sales trends, and music preferences using SQL queries. This helps simulate real-world business insights that data analysts might uncover in a retail music company.

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📌 Project Highlights

• ✅ ** Real-world SQL Queries** solving business problems.
• ✅ Used advanced JOINs, CTEs, Window Functions, Subqueries.
• ✅ Focused on customer behavior, genre trends, artist popularity, and regional sales.
• ✅ Hands-on experience with analytical thinking and SQL optimization.

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🧠 Problem Statements Solved(In Breif)

1. Who is the best customer?
   → Found the customer who spent the most across all invoices.

2. Which city has the best customers?
   → Identified the city with the highest invoice revenue for promotional targeting.

3. Top 10 Rock artists.
   → Ranked bands based on the number of Rock genre tracks.

4. Which country has the most invoices?

5. Top 3 highest invoice totals.

6. What is the most popular genre in each country?

7. Find customers who listen to Rock music.

8. Customers' total spend on the top artist.

9. Tracks longer than average length.

10. Who spent the most on music by country?
    → Used ROW_NUMBER() window function for each country group.

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📁 Technologies Used

Tool	Purpose
SQL	Data querying and analysis
Git	Version control
Markdown	Documentation

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📸 Project Screenshots

Replace the image links with your actual screenshots after uploading them in your repo’s folder (/images or /assets)

🔹 Best Customers by Country

🔹 Rock Music Listeners Query

🔹 Most Popular Genre by Country

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📊 Key Learnings

• Learned how to structure SQL queries to solve business questions.
• Understood the power of CTEs and Window Functions for advanced reporting.
• Practiced subquery optimization and join techniques for efficient data retrieval.
• Strengthened data storytelling using structured SQL outputs.

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🚀 How to Use

1. Clone the repository.
2. Open the .sql file in any SQL editor (DB Browser, DBeaver, etc.)
3. Load the music store SQLite database.
4. Run queries one-by-one to explore and understand the business insights.

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📬 Contact

If you have any questions, feel free to connect:

👨‍💻 Mukesh Kumar
📧 [muk.786422@gmail.com]
🔗 [LinkedIn:https://www.linkedin.com/in/kumarmukesh95/)]

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🌟 If you like this project...

Give it a ⭐️ on GitHub or share it with others who want to practice SQL in real-world projects!