Ruth-Kasina/Maji-Ndogo-Project

# Maji Ndogo Water Access Analysis > An end-to-end data analytics project assessing water accessibility across five provinces in Maji Ndogo — uncovering infrastructure gaps, contamination risks, and disparities between urban and rural communities. --- ## Project Overview Access to clean water is a fundamental need, yet millions remain underserved due to aging infrastructure, geographic barriers, and resource constraints. This project analyses water source data collected across **200 survey points** in Maji Ndogo to answer critical questions: - Which communities lack access to clean, reliable water? - Where are queue times dangerously long? - Which infrastructure sites are overdue for repair? - How do urban and rural areas compare in water quality and access? --- ## Tools Used | Tool | Purpose | |------|---------| | **Excel** | Data storage, summary tables, and KPI calculations | | **SQL (MySQL)** | Data cleaning, exploration, and multi-table analysis | | **Power BI** | Interactive dashboard and visualisations | --- ## Dataset Description **File:** `Maji_Ndogo_Water_Dataset.xlsx` The workbook contains three sheets: | Sheet | Description | |-------|-------------| | `Water_Sources_Raw` | 200 raw records across 5 provinces and 15 towns | | `Summary_Analysis` | Aggregated metrics by source type, urban/rural split, and infrastructure status | | `Province_KPIs` | Province-level KPIs including contamination rate, avg queue time, and quality score | **Key columns:** - `Water_Source_Type` — Tap in Home, Shared Tap, Well, River, Borehole, etc. - `Population_Served` — number of people relying on each source - `Queue_Time_min` — average wait time in minutes at the source - `Water_Quality_Score` — score from 1.0 (very poor) to 10.0 (excellent) - `Contamination_Flag` — Yes / No flag based on quality threshold - `Infrastructure_Status` — Functional / Needs Repair / Non-Functional / Under Construction --- ## SQL Analysis Structure **File:** `maji_ndogo_analysis.sql …