Slyza13/Data-Visualization-Project-1

This phase transforms the Maji Ndogo water crisis SQL analysis into interactive Power BI dashboards, revealing new insights about gender roles, infrastructure priorities, and queue patterns. 📊 Maji Ndogo Water Crisis Analysis – Data Visualization Project (Power BI) # Maji Ndogo Water Crisis Analysis (Part 1 - Power BI) 📝 Short Description This phase transforms the Maji Ndogo water crisis SQL analysis into interactive Power BI dashboards, revealing new insights about gender roles, infrastructure priorities, and queue patterns. It builds on the cleaned database from Parts 1–4 and makes findings accessible to both technical and non-technical stakeholders. 🎯 Project Overview Goal: Convert raw SQL findings into visual, stakeholder-friendly insights. Scope: Interactive dashboards for national, provincial, and community-level analysis. Dataset: Extended survey database with AI-enhanced queue composition (gender & age percentages). 🔧 Key Visualizations 🌍 National-Level Dashboard Urban vs. rural population distribution (Pie) Water source type breakdown (Bar) Cross-filtering between all visuals Total population served: ~28M citizens 🗺 Geographical Analysis Custom Maji Ndogo province map (JSON integration) Infrastructure issues by province & town Interactive province selection for drill-down insights ⏱ Queue Time Analysis Daily & hourly queue trends Gender composition analysis (male, female, children) Weekend vs. weekday comparison Relationship between queue time and population served ⚙️ Technical Implementation Power BI Features: Custom maps with JSON & shape overlays Cross-filtering & drill-down interactivity Pie, bar, line, scatter, and clustered visuals Data Preparation: Validated percentage fields (percent_male, percent_female, percent_child) Deduplicated visit counts to ensure accuracy Configured regional maps for unfamiliar geographies 📈 Critical Insights Gender Roles: Women dominate weekday water collection; men participate more on weekends. Children’s Burden: Children frequently accompany mothers, affecting education & safety. Queue Dynamics: Saturdays = worst wait times (246 min avg vs 82–137 weekdays). Regio …