dawo-web/Water-in-Africa-Analytics

Analyzing water accessibility and sanitation data in Africa using SQL. # Africa Water Accessibility Analysis 🌍💧 ## Project Goal Analyze clean water accessibility across African countries to identify regions needing urgent intervention. ## Tools Used - **SQL** (Data querying and analysis) - **Excel** (Data cleaning and basic visualization) - **Power BI** (for advanced visuals) ## Data Sources - Sample dataset: Mock data for demonstration World Bank Data World Bank Open Data - Real-world dataset idea: UNICEF Water Scarcity in Africa. ## SQL Analysis Steps 1. **Filtering**: Identified countries with water access below 60%. 2. **Aggregation**: Calculated regional average water access. 3. **Calculations**: Estimated populations without clean water access. ## Key Findings - Ethiopia has the lowest clean water access (45%). - Southern Africa has the highest average access (85%). ## How to Reproduce 1. Clone this repository. 2. Run `scripts/water_analysis.sql` in any SQL environment (e.g., PostgreSQL, MySQL). 3. View results in the `outputs/` folder. *(Optional: Add your chart here)* ## Advanced SQL Techniques - **Joins**: Combined water access and population data for deeper insights. - **Window Functions**: Ranked countries by water stress levels. - **CTEs & ROLLUP**: Created regional summaries and temporal comparisons.