Welcome to my SQL-based analytics project using the Chinook Database, a digital music store simulation. This case study explores customer behavior, sales performance, and strategic opportunities using structured SQL queries.
- Database: Chinook simulates a digital music store with tables for Customers, Invoices, InvoiceLines, Tracks, Albums, Artists, and Employees.
- Goal: Use SQL to extract insights about customer demographics, purchasing patterns, employee performance, and regional sales distribution.
- 🧑💼 Top-Spending Customers – Identify high-value contributors across countries
- 🌍 Sales by Region – Compare revenue by city and country
- 🎶 Genre & Artist Affinity – Discover co-purchase patterns for bundling strategies
- 📈 Customer Lifetime Value – Analyze average order value and retention signals
⚠️ Churn Rate – Flag inactive customers and suggest retention campaigns- 🎯 Promotional Strategy – Recommend albums and genres for targeted marketing
- 🐘 SQL (MYSQL) – Joins, subqueries, aggregations, window functions
- 📊 Excel – Audit templates, categorization logic, KPI tracking
- 🧠 Business Intelligence – Strategic recommendations based on data patterns
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Chinook Query File.sql– All SQL queries used for analysis -
Chinook Presentation.pptx– Visual presentation of insights and strategy -
SQL Doc File.docx– Written documentation of findings and recommendations
Special thanks to Asif Iqbal, my SQL instructor at Newton School, for his mentorship and guidance throughout this project.
Open to feedback and suggestions! Feel free to fork the repo or raise issues.