🎵 Music Store SQL Analysis

This project analyzes a digital music store database using PostgreSQL.
The database contains information about employees, customers, invoices, tracks, playlists, artists, albums, and more.
Through SQL queries, we explore sales trends, customer behavior, popular genres, top artists, and revenue insights.

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🛠️ Tools & Technologies

• PostgreSQL
• SQL (queries, joins, aggregations, subqueries)
• pgAdmin / psql (for running queries)
• Git & GitHub for version control

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📂 Project Files

• music_store_csv.zip → Contains all 11 dataset files in CSV format
• schema_diagram.png → ER diagram showing relationships between tables
• Create_table_query.sql → SQL queries to create tables
• Questions.txt → Business/analysis questions
• Answers.sql → SQL queries answering the analysis questions

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🗄️ Database Schema

The database has 11 tables:

• Employee → Employee details
• Customer → Customer info
• Invoice → Purchase invoices with billing details and total
• Invoice_Line → Details of tracks purchased in each invoice
• Track → Tracks information
• Playlist → Music playlists
• Playlist_Track → Mapping between playlists and tracks
• Artist → Artist information
• Album → Albums created by artists
• Media_Type → File/media type of tracks
• Genre → Music genres

📌 See schema_diagram.png for a complete Entity-Relationship diagram.

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🚀 How to Run

1. Clone this repository:

   git clone https://github.com/Harsh-Belekar/Music-Store-SQL-Analysis.git

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📧 Contact

🔗 LinkedIn – Harsh Belekar