📘 COVID-19 Global Monitoring Dashboard

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🧾 1. Project Overview

This project provides a real-time automated COVID-19 tracking system. It leverages public health data APIs and automates the full ETL workflow—from extraction to visualization—offering an interactive Power BI dashboard for global monitoring.

• API: disease.sh
• ETL: Python + SQLite + MS Excel
• Visualization: Microsoft Power BI
• Automation: Windows Task Scheduler with .bat file

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❓ 2. Business Questions Addressed

• Which countries are the most and least affected by COVID-19?
• What is the global recovery rate vs. death rate?
• How is the active vs. recovered vs. deceased case distribution?
• What are today's new cases across the world?
• How do outbreak patterns evolve over time?

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📊 3. Data Analysis

✅ Dataset Fields:

• country, cases, todayCases, deaths, todayDeaths
• recovered, todayRecovered, active, critical, population
• fetch_date (auto-refreshed daily)

📡 Data Source:

• API Endpoint: https://disease.sh/v3/covid-19/countries
• Refreshed and logged daily using Python → SQLite → Excel

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📈 4. Visualizations (Power BI)

Component	Description
KPI Cards	Global stats: Total Cases, Deaths, Recovered, Population, Last Updated
Line Chart	Daily new cases trend across all countries
Bar Chart	Top 10 countries by total COVID cases
Clustered Bars	Death Rate vs. Recovery Rate by Country
Pie Chart	Proportion of Active, Recovered, and Deaths globally
Filled Map	World map colored by total cases
Slicers	Filters by Country, Population, and Date

📁 Power BI File:
🔗 Visualisation/Visualiastion of covid data.pbix

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🧠 5. Key Insights

• U.S., India, Brazil have the highest case volume.
• Many countries show high recovery rates (>80%).
• Smaller countries may have higher per capita impact.
• Map and pie charts effectively convey global distribution.
• Trends help anticipate outbreak waves and effectiveness of control measures.

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⚙️ 6. Tech Stack

Tool	Purpose
Python	ETL, API integration, data cleaning
Pandas	Data wrangling and transformation
SQLite	Lightweight DB for historical data tracking
Power BI	Interactive dashboards & stakeholder reports
Windows Scheduler	Automate daily script execution

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🛠️ 7. Automation & Maintenance

• 🧠 Script:
  Notebook and scripts/covid_auto_fetch.py

• ⚙️ Batch File:
  Notebook and scripts/covid_auto_fetch_script.bat

• 📅 Scheduled With:
  Windows Task Scheduler (runs script every day automatically)

• 📂 Daily Output:

  • Live covid19 dataset/covid_data.db
  • Live covid19 dataset/covid_data_exported.xlsx
  • Log files/log.txt
  • Log files/error_log.txt

✅ The pipeline ensures the Excel and SQLite DB are updated daily with minimal manual effort.

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📁 8. Project Structure

📦 Live-Covid19-Project
│
├── 📂 Live covid19 dataset
│   ├── covid\_data.db
│   └── covid\_data\_exported.xlsx
│
├── 📂 Log files
│   ├── log.txt
│   └── error\_log.txt
│
├── 📂 Notebook and scripts
│   ├── covid\_auto\_fetch.py
│   ├── covid\_auto\_fetch\_script.bat
│   ├── covid\_data.ipynb
│   └── EDA covid data.ipynb
│
├── 📂 Visualisation
│   └── Visualiastion of covid data.pbix
│
├── 📂 Report
│   └── COVID19\_Global\_Dashboard\_Report.pdf
│
├── 📄 Dashboard.png
└── 📄 README.md

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📌 9. Recommendations

• Add moving averages for smoother trends.
• Include cases per million population for fairness.
• Add conditional formatting in KPIs (e.g., red for rising cases).
• Use Power BI Service to publish interactive dashboards online.
• Introduce alerts when cases spike or threshold is crossed.

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🏁 10. Conclusion

This project is a strong showcase of full-stack data skills—ideal for data analyst and BI developer roles:

• ✅ API Integration & ETL
• ✅ Real-time data pipelines
• ✅ SQLite + Excel syncing
• ✅ Power BI dashboarding
• ✅ End-to-end automation

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🔗 Connect with Me

• 🌐 GitHub Profile
• 💼 LinkedIn
• 👨‍💻 HackerRank

💬 Feel free to fork this repo or reach out for collaborations or suggestions!