This project presents an end-to-end business analysis of the Chinook Music Store database using SQL. The objective is to analyze sales performance, customer behavior, and product trends by answering business-focused questions using real transactional data.
Rather than focusing solely on SQL syntax, this project demonstrates how SQL can be applied to extract meaningful insights and support data-driven business decisions through clear analysis and actionable recommendations.
This analysis aims to answer the following business questions:
- What is the company's total revenue?
- Which countries and cities generate the highest revenue?
- Who are the highest-value customers?
- Which music genres, artists, and albums perform best?
- How can business performance be improved through data-driven recommendations?
Database: Chinook SQLite Database
The Chinook database simulates a digital music store and contains transactional data related to customers, invoices, employees, artists, albums, tracks, playlists, and genres.
| Metric | Value |
|---|---|
| Customers | 59 |
| Invoices | 412 |
| Invoice Line Items | 3,503 |
| Countries | 24 |
| Database | SQLite |
Throughout this project, the following SQL concepts were applied:
- SELECT statements
- Filtering using WHERE
- Aggregate Functions (
SUM,AVG,COUNT) - GROUP BY
- ORDER BY
- INNER JOIN
- Multi-table JOINs
- Window Functions (
RANK) - Business KPI Analysis
- Data Aggregation
- Total company revenue
- Revenue by country
- Revenue by city
- Average invoice value
- Monthly revenue trend
- Top customers by spending
- Customer distribution by country
- Customers with the highest number of purchases
- Average customer spending
- Customer ranking by revenue
- Highest revenue-generating genres
- Top-performing artists
- Highest revenue-generating albums
- Most purchased tracks
- Most popular media types
- Generated 2,329.00 in total revenue across 412 invoices.
- The United States generated the highest revenue (523.06), making it the strongest-performing market.
- Prague was the highest revenue-generating city (90.24).
- Rock was the highest-performing genre, generating 826.65 in revenue—more than twice that of the second-ranked genre.
- Iron Maiden generated the highest artist revenue (138.60).
- The average invoice value was 5.65, indicating relatively small individual transactions.
Based on the analysis, the following recommendations are proposed:
- Continue investing in the United States, the company's strongest revenue-generating market.
- Expand the Rock music catalog and related marketing campaigns to capitalize on sustained customer demand.
- Introduce customer loyalty or rewards programs targeting high-value customers.
- Increase promotional activities in high-performing cities to strengthen customer engagement.
- Improve the average invoice value through product bundles, cross-selling, and personalized recommendations.
- SQL
- SQLite
- DB Browser for SQLite
- Visual Studio Code
- Git
- GitHub
SQL-Chinook-Analysis/
│
├── README.md
├── queries.sql
├── insights.md
│
├── database/
│ └── Chinook_Sqlite.sqlite
│
└── screenshots/
├── database_schema.png
├── revenue_by_country.png
└── top_customers.png
- Clone or download this repository.
- Open the
database/Chinook_Sqlite.sqlitedatabase using DB Browser for SQLite. - Execute the SQL queries from
queries.sql. - Review the analysis and business insights in
insights.md.
This project demonstrates how SQL can be used to analyze business performance using a relational database. By combining SQL queries with business interpretation, the analysis transforms raw transactional data into actionable insights that can support informed business decisions.
This project was completed as part of my data analytics learning journey to strengthen my SQL, analytical thinking, and business problem-solving skills.
Rather than simply writing SQL queries, I focused on communicating insights, identifying trends, and providing practical business recommendations—skills that are essential for real-world data analysts.