This project focuses on analyzing a newly collected database of 60,000 records for Maji Ndogo Water Services.
The data, gathered by engineers, scientists, field workers, and analysts, holds crucial insights to address the region’s ongoing water crisis.
The goal is to explore, clean, and analyze this extensive dataset to uncover patterns, identify challenges, and support data-driven decision-making.
As part of the project, I broke down the work into actionable steps:
- Data Familiarization – Load and inspect all tables to understand structure, relationships, and variables.
- Water Source Analysis – Identify all unique water source types and their distributions.
- Visit Pattern Exploration – Analyze visit frequencies to different sources and flag high-traffic locations.
- Water Quality Assessment – Filter sources with high subjective quality scores and frequent visits.
- Pollution Investigation – Identify contaminated sources requiring urgent intervention.
By executing these tasks, I translate raw data into meaningful insights that can guide interventions, improve infrastructure planning, and ultimately bring Maji Ndogo closer to resolving its water crisis.
Skills Applied: SQL · Data Exploration · Data Cleaning · Filtering · Conditional Queries · Pattern Detection
Check here for details.