🌍 Exploring the World with SQL:

As someone passionate about data analysis, I wanted to challenge myself with a project that demonstrates real-world analytical thinking using SQL. For this, I turned to the classic world database, a publicly available dataset containing information on countries, cities, and languages around the globe.

🔍 The Challenge

How can we extract meaningful insights from raw geographic and demographic data using only SQL?

Rather than just running a few queries, I approached this like a mini data investigation — posing questions, framing them into SQL problems, and interpreting the answers. Each query became a stepping stone in understanding how to structure, filter, and join relational data.

🛠️ The Tools

• MySQL for writing and executing SQL queries

• world.sql database (city, country, and language tables)

📊 Key Insights Discovered

1. How many cities are listed in the USA?
→ I learned how to count entries with WHERE filters.

2. Which country has the highest life expectancy?
→ Using ORDER BY and LIMIT, I quickly ranked all nations.

3. Which cities start with “Be”?
→ Pattern matching (LIKE 'Be%') revealed naming conventions across cultures.

4. What are the 10 most populous cities globally?
→ This was a simple sort, but it gave context on urban population distribution.

5. What’s the average city population per country?
→ Grouping and joining tables helped me spot countries with more urbanized populations.

6. Which cities exist in Europe? And what’s the capital of Spain?
→ These queries were a great exercise in joining foreign keys across the city and country tables.

7. Which countries have the lowest population density?
→ I calculated custom metrics (Population / SurfaceArea) — a real-world use case for derived fields.

8. Which cities have a higher-than-average GDP per capita?
→ This was the most advanced query: combining JOIN, WHERE, AVG(), and a nested subquery.

9. Can we rank cities beyond just the top 10?
→ Using OFFSET and ROW_NUMBER(), I implemented SQL-based pagination — an essential concept in web and dashboard applications.

💡 What I Gained

This project helped me strengthen my ability to:

• Write clean, logical SQL queries

• Ask data-driven questions and answer them with code

• Use joins, aggregations, subqueries, and calculated fields

• Communicate findings in a clear, organized way

📁 View the Full Project on GitHub

You can explore the full SQL breakdown, queries, explanations, and code structure here:
🔗 GitHub Repository – WorldDBSQL