Toluwanimi-D-A/Water-Accessibility-in-Africa

A SQL-based data analysis case study assessing water availability, sanitation infrastructure, and public health in African communities, with recommendations for improving service delivery. # Water Access and Sanitation in Africa (SQL Case Study). A SQL-based data analysis case study assessing water availability, sanitation infrastructure, and public health in African communities, with recommendations for improving service delivery. # Project Overview -A Capstone project leveraging SQL to explore challenges in water access and sanitation across African countries using relational database analysis techniques. It focuses on identifying operational issues, health outcomes, and support efforts. # Objective -To uncover patterns in water availability, sanitation quality, and community health, and to support targeted interventions by NGOs and governments. # Tools & Technologies - MySQL - SQL Workbench / DB Browser - Microsoft Word # Datasets Analyzed - Water source type & functionality - Sanitation facilities and maintenance cost - NGO and government support - Health outcomes and disease incidence - Population and community satisfaction # Key SQL Tasks - Calculate average water availability per capita - Identify non-functional water points - Analyze disease prevalence and sanitation issues - Find communities receiving both government and NGO support # Project Structure /data → Structured datasets (.csv) /sql-scripts → SQL queries used in the project /insights → Output tables, screenshots, or brief summaries # Outcome A comprehensive SQL-driven analysis offering insights into improving water and sanitation infrastructure and public health outcomes in Africa. # Personal Reflection Working with SQL in this project helped me appreciate the power of querying real-world data. Writing SQL that translated into meaningful community-level insight was incredibly rewarding. The challenge was staying organized across multiple related tables, but it taught me how to structure queries and make my code reusable. I also realized how critical clean, reliable data is to good decision-making.