SQL-International_Debt_Analysis

Using SQL, cleaning and querying data in a way one can use it for gathering insights

SUMMARY:

Overall, this project provides good practice for using more advanced SQL skills like window functions, common table expressions, subqueries, and complex joins to analyze a real-world multivariate dataset and derive business insights. The code is well commented to explain the approach.

KEY POINTS:

• Goal: Use SQL to analyze international debt data from The World Bank
• Skills: Joins, CTEs, temp tables, window functions, aggregation, subqueries
• Data: Country debt indicators from multiple tables like country, loan, indicator etc.
• Analysis: Questions explore total debt, average debt growth, highest debt in regions, debt by income level
• Approach: Joins between tables, aggregations with GROUP BY, window functions like ROW_NUMBER() and LAG(), CTEs and temp tables to break down complex queries
• Outcomes: Practiced complex SQL analysis on real international economic data, derived insights like top 5 debt countries, regional debt patterns, debt growth rate changes