Clustering data to unveil Maji Ndogo's water crisis
# SQL PROJECT 2 | π§ Maji Ndogo Water Crisis β Turning Data into Community Insights
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## π€ Author
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**Omotola Lawal**
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12th June, 2025
π LinkedIn
## π Table of Contents
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1. π Project Overview β Setting the stage for our data exploration journey
2. ποΈ Cleaning Our Data β Updating employee data
3. π Honouring the Workers β Finding our best
4. π Analysing Locations β Understanding where the water sources are
5. π¦ Diving into the Sources β Seeing the scope of the problem
6. π οΈ Start of a Solution β Thinking about how we can repair
7. π Analysing Queues β Uncovering when citizens collect water
8. π Reporting Insights β Assembling our insights into a story
9. π οΈ Practical Solutions β Recommendation
10. π Reference
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## πProject Overview β Setting the stage for our data exploration journey
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This project is personal to me because it goes beyond running SQL queries β itβs about telling the story of the **Maji Ndogo water crisis** through data.
When I first explored the dataset, I didnβt just see rows and columns. I saw communities waiting in long queues, families depending on unsafe water, and field workers trying their best to bridge a massive gap.
Hereβs how I approached it:
- I started by **cleaning and validating the data** to make sure the foundation was trustworthy.
- Then, I used **clustering and aggregation** to uncover the bigger narratives hidden beneath isolated records.
- I treated each data point as someoneβs lived experience β not just a number β which made **integrity checks and auditing** essential.
- Finally, I zoomed in on both **granular details** (individual sources, employees, queues) and the **big picture** (provincial coverage, quality, and availability).
For me, this project isnβt just about technical SQL skills. Itβs about showing how **data can become a voice** β turning hidden patterns into insights that can guide real-world solutions for the communities who need them most.
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**Skills Applied:** SQL Β· Data Aggregation Β· Cou β¦