A data analysis project for Alx data science program.
# Maji Ndogo Water Access Project: Unveiling the Crisis through Data
## Overview
This repository contains the data analysis project focused on understanding and addressing the water crisis in Maji Ndogo. The project leverages a comprehensive dataset of water source visits, quality assessments, and employee activities to identify patterns, clean data, and derive actionable insights.
The work is structured into multiple phases:
1. **Phase 1: Initial Data Exploration & Quality Assessment (Maji Ndogo Part 1)**
- Familiarization with foundational tables and their interconnections.
- Initial assessment of data quality and identification of anomalies.
- Basic analytical queries to understand existing conditions.
2. **Phase 2: Data Cleaning, Deeper Analysis & Clustering (Maji Ndogo Part 2)**
- Extensive data cleaning and transformation to ensure data integrity.
- Detailed analysis of employee performance and location-based patterns.
- Preparation for clustering techniques to uncover broader narratives and hidden correlations related to water access and quality.
3. **Phase 3: Weaving the Data Threads of Maji Ndogo’s Narrative (Maji Ndogo Part 3)**
- Validate the integrity of subjective water quality scores submitted by employees.
- Identify potential data manipulation or systemic issues.
- Use SQL to trace inconsistencies to specific employees and locations.
4. **Phase 4: From Analysis to Action (Maji Ndogo Part 4)**
- Combine survey, water quality, and pollution data into a unified view for planning.
- Summarize water source conditions by province and town.
- Recommend specific engineering interventions for contaminated or inadequate sources.
- Create and populate a `Project_progress` table to track repair initiatives with conditional SQL logic.
- Assign improvements based on contamination type, water source condition, and queue time patterns.
## 📌 Objectives
The primary objectives of this project are to:
- **Understand Data Structure:** Gain a deep understanding …