This project analyzes a music store database using SQL to uncover insights into customer behavior, music trends, and business performance.

Key areas of analysis include:

Customer purchasing behavior and spending patterns Best-selling tracks, albums, and revenue trends Genre-wise and artist-wise performance analysis Song attributes such as length and their impact on popularity A simulated music festival scenario to evaluate demand and revenue behavior

To solve complex analytical questions, I used advanced SQL techniques such as:

Joins for combining multiple tables CTEs (Common Table Expressions) for structured query breakdown Recursive queries for hierarchical or iterative data exploration Aggregations and subqueries for deep insights

This project demonstrates how SQL can be used to transform raw data into meaningful business intelligence.