amogelangseipone/SA-Unemployment-Analysis

Power BI report analyzing South African unemployment disparities between youth (15-24) and adults (25+) from 2000-2024. Created in Power BI Desktop with data cleaning, DAX measures, and interactive visualizations showing youth unemployment is 2.1x higher. # South Africa: Youth vs Adult Unemployment Analysis (2000-2024) ## 📊 Project Overview An interactive Power BI dashboard analyzing two decades of unemployment trends in South Africa, revealing significant disparities between youth (15-24) and adult (25+) employment rates. This project demonstrates end-to-end data analysis from raw data preparation to actionable insights. ## 🎯 Key Findings - **2.1x Higher**: Youth unemployment (60.1%) is 2.1 times higher than adult unemployment (28.9%) - **31.2% Gap**: Persistent 31.2 percentage point difference between age groups - **COVID-19 Impact**: Both groups peaked during 2020 pandemic period - **Structural Issue**: Gap persists across 24-year timeframe despite economic changes ## 🔧 Technical Implementation | Component | Tools Used | Key Features | |-----------|------------|--------------| | **Data Preparation** | Power Query | Filtered to South Africa, removed 1000+ irrelevant rows and 6 columns | | **Data Modeling** | Power BI Desktop | Clean star schema, optimized relationships | | **Calculations** | DAX Measures | Unemployment gap, youth-adult ratio, year-over-year analysis | | **Visualization** | Power BI Charts | Interactive line chart, KPI cards, year range slicer | ## 🚀 How to Explore 1. **Download** the `.pbix` file 2. Open in **Power BI Desktop** (free download) 3. **Interact** with the year range slicer (2000-2024) 4. **Hover** over charts for detailed tooltips 5. **Analyze** the DAX measures in the modeling view ## 📈 Business Impact This analysis helps stakeholders: - Understand severity of youth unemployment crisis - Track effectiveness of youth employment programs - Identify economic vulnerability periods - Make data-driven policy decisions ## 🛠️ Skills Demonstrated - **Data Cleaning** with Power Query - **DAX Measure** development - **Interactive Dashboard** design - **Data Storytelling** with insights - **End-to-end** analytics workflow ## 📚 Data Source International Labour Organization (ILO) - ILOSTAT …