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lawaloa/SQL_Project_2

Domaine:

environment and energy
Créateur:
law
Hôte:
Clustering data to unveil Maji Ndogo's water crisis # SQL PROJECT 2 | 💧 Maji Ndogo Water Crisis – Turning Data into Community Insights --- ## 👤 Author --- **Omotola Lawal** 📅 12th June, 2025 🔗 LinkedIn ## 📑 Table of Contents --- 1. 📘 Project Overview – Setting the stage for our data exploration journey 2. 🗂️ Cleaning Our Data – Updating employee data 3. 🙌 Honouring the Workers – Finding our best 4. 🌍 Analysing Locations – Understanding where the water sources are 5. 💦 Diving into the Sources – Seeing the scope of the problem 6. 🛠️ Start of a Solution – Thinking about how we can repair 7. 📊 Analysing Queues – Uncovering when citizens collect water 8. 📝 Reporting Insights – Assembling our insights into a story 9. 🛠️ Practical Solutions – Recommendation 10. 📑 Reference --- ## 📘Project Overview – Setting the stage for our data exploration journey --- This project is personal to me because it goes beyond running SQL queries — it’s about telling the story of the **Maji Ndogo water crisis** through data. When I first explored the dataset, I didn’t 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. Here’s 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 someone’s lived experience — not just a number — 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 isn’t just about technical SQL skills. It’s about showing how **data can become a voice** — turning hidden patterns into insights that can guide real-world solutions for the communities who need them most. ✅ **Skills Applied:** SQL · Data Aggregation · Cou …

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