🎵 Music Store Data Analysis

📌 Project Overview

This project, Music Store Data Analysis, focuses on extracting valuable insights from a music store database. The database includes information about:

• Customers – Purchase patterns and demographics
• Employees – Sales representatives and their performance
• Invoices – Sales transactions and revenue tracking
• Tracks & Artists – Best-selling songs and popular artists
• Genres & Playlists – Music trends and customer preferences

Using SQL queries, we analyze various aspects of the store’s operations.

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🛠 Tech Stack & Tools

• Database: PostgreSQL / MySQL
• Query Language: SQL
• Data Analysis: Aggregation, filtering, and trend detection

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📊 SQL Analysis Queries

🔹 Top-Selling Tracks

SELECT Track.Name, SUM(Invoice_Line.Quantity) AS TotalSales
FROM Invoice_Line
JOIN Track ON Invoice_Line.Track_Id = Track.Track_Id
GROUP BY Track.Name
ORDER BY TotalSales DESC
LIMIT 10;

  Revenue by Genre
 SELECT Genre.Name, SUM(Invoice_Line.Unit_Price * Invoice_Line.Quantity) AS Revenue
FROM Invoice_Line
JOIN Track ON Invoice_Line.Track_Id = Track.Track_Id
JOIN Genre ON Track.Genre_Id = Genre.Genre_Id
GROUP BY Genre.Name
ORDER BY Revenue DESC;


🔹 Employee Sales Performance
SELECT 
 Employee.First_Name, 
 Employee.Last_Name, 
 SUM(Invoice.Total) AS TotalSales
FROM Invoice
JOIN Customer ON Invoice.customer_id = Customer.customer_id
JOIN Employee ON CAST(Customer.support_rep_id AS INTEGER) = CAST(Employee.employee_id AS INTEGER)
GROUP BY Employee.First_Name, Employee.Last_Name
ORDER BY TotalSales DESC;


🚀 How to Use
1️⃣ Clone the repository:
git clone <repository_url>
2️⃣ Import the database schema (schema.sql & data.sql) into your PostgreSQL or MySQL database.
3️⃣ Run SQL queries from queries.sql to analyze the dataset.

📬 Contact & GitHub
For any questions or suggestions, feel free to reach out:

👤 Name: Vaibhav Anand
📧 Email: anandvaibhav02@gmail.com