A Power BI data visualisation project exploring gender disparities, crime risks, and public water funding transparency in Maji Ndogo β transforming data into insights that support social impact and better community decision-making.
## Visualizing Data Project β Part 1
This project explores the state of **water access** across communities in **Maji Ndogo**, highlighting:
- Infrastructure issues
- Queue wait times
- Spatial accessibility disparities
- **Gender inequality** in water collection
The analysis uses real survey data enhanced with **AI-based image classification**, identifying the demographic composition of water queues.
π Project Overview
Field surveyors collected water source data and queue observations at multiple locations in Maji Ndogo.
Using **machine learning**, photographs taken onsite were analyzed to detect and classify:
- Men π§ββοΈ
- Women π§ββοΈ
- Children π§
This revealed who carries the burden of collecting water β **women and children**, especially in unsafe hours.
The insights are presented using **interactive Power BI dashboards**, designed to support:
- National & local government planning
- NGO & donor infrastructure funding decisions
- Strategic initiatives for **gender equity** in resource access
π― Key Insights
From SQL analysis and updated datasets:
- Majority of citizens rely on **rural water sources**
- **43%** use **shared taps** β up to **2000 people sharing one**
- **31%** have in-home taps β but **45% are dysfunctional**
- **18%** use wells β only **28% are clean**
- Queues often exceed **120 minutes**
β± Queue Time Peaks
- Longest: **Mornings, evenings, Saturdays**
- Shortest: **Wednesdays & Sundays**
π©βπΌ Gender + Age Burden
- Women & children dominate queue participation
- Men contribute more **only on weekends**
π Tools Used
| Tool | Purpose |
|------|---------|
| Power BI | Interactive dashboards & visual storytelling |
| GIS & Custom Maps | Location-based insights |
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## Visualizing Data Project β Part 2
This project is the **second phase** of the Maji Ndogo Water Access Visualization initiative.
While **Part 1** focused on understanding *where* and *why* water access problems exist, **Part 2** focuses on **what should be done next** β¦