🌍 Global Economic and Financial Analytics

Features

• Synthetic Data Generation: SQL scripts to create and populate financial table

📌 Overview

This project analyzes global economic indicators, financial markets, and stock performance using SQL. The database is structured with multiple interconnected tables to model financial data efficiently, enabling insights through advanced SQL queries.

Folder and File Structure

• tables.sql This file produces the tables for the sql analysis.
• main.sql This contains all the sql structure functions to create the queries. Thus, generating the synthetic data for the tables and sql dataset.
• /Screenshots This folder contains all the screenshots that were taken during the sql operations and functionalities. Thus, the creation of new tables, inserting and analysis.

📊 Database Schema

The database consists of multiple tables covering:

• Countries 🌎 (GDP, inflation, unemployment, trade balance, etc.)
• Stock Markets 📈 (Index performance, volatility, trading volume, etc.)
• Currencies 💱 (Exchange rates, currency reserves, stability metrics, etc.)
• Interest Rates 📉 (Central bank rates, bond yields, etc.)
• Economic Indicators 📊 (Consumer spending, industrial production, etc.)

Entity-Relationship Diagram (ERD)

📌 (Include an ERD image or schema diagram here)

🛠️ Setup & Installation

1️⃣ Clone the Repository:

git clone https://github.com/kw3ku/Sql-global-economic-financial-analytics.git
cd Sql-global-economic-financial-analytics

2️⃣ Import the Database in DBeaver:

• Open DBeaver
• Connect to your SQL database (PostgreSQL/MySQL/SQLite)
• Run the SQL scripts in /schema/

3️⃣ Insert Sample Data:

-- Example: Table structure
CREATE TABLE economic_indicators (
    indicator_id SERIAL PRIMARY KEY,
    country_id INT REFERENCES countries(country_id),
    year INT NOT NULL,
    gdp NUMERIC(15,2),
    inflation_rate NUMERIC(5,2),
    trade_balance NUMERIC(15,2),
    UNIQUE (country_id, year)
);

CREATE TABLE exchange_rates (
    rate_id SERIAL PRIMARY KEY,
    country_id INT REFERENCES countries(country_id),
    currency_code CHAR(3) NOT NULL,
    year INT NOT NULL,
    exchange_rate NUMERIC(10,4),
    UNIQUE (country_id, currency_code, year)
);

-- Example: Insert sample GDP data
INSERT INTO Countries (id, name, gdp, inflation, unemployment_rate) VALUES
(1, 'USA', 25000000, 3.2, 4.1),
(2, 'Germany', 4200000, 2.8, 3.5),
(3, 'Japan', 5100000, 1.1, 2.9);

🔍 Key SQL Queries

✅ Find Top 5 Countries by GDP:

SELECT name, gdp FROM Countries ORDER BY gdp DESC LIMIT 5;

✅ Track Stock Market Trends Over Time:

SELECT country_id, year, avg(stock_index) FROM StockMarkets GROUP BY country_id, year ORDER BY year DESC;

✅ Analyze Inflation Impact on Interest Rates:

SELECT c.name, e.inflation, i.interest_rate 
FROM Countries c
JOIN EconomicIndicators e ON c.id = e.country_id
JOIN InterestRates i ON c.id = i.country_id
ORDER BY e.inflation DESC;

📈 Insights & Findings

📌 Summarize key insights here, e.g.,

• Countries with higher inflation tend to have higher interest rates.
• Stock market volatility increases during financial crises.
• Strong foreign reserves help stabilize currency fluctuations.

🔥 Future Enhancements

• Integrate real-world financial APIs (e.g., World Bank, Yahoo Finance)
• Implement visualizations using Python/Power BI
• Optimize SQL queries for faster performance

📜 License

This project is open-source under the MIT License.

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🚀 Contributions are welcome! If you have suggestions or improvements, feel free to fork and create a pull request! 🔥