A Project Management Case Study in Data Engineering for Cybersecurity
A complete ETL pipeline that analyzes security incidents and generates interactive dashboards. Built to demonstrate the intersection of:
- Technical skills (Python, SQL, data visualization)
- Project Management (planning, documentation, methodology)
- Business Intelligence (KPIs, dashboards, storytelling)
- Cybersecurity domain knowledge
Analyzes 100 security incidents showing:
-
Total incidents and severity breakdown
-
Cost impact ($5M+)
-
Response time metrics
-
Trends over 30 days
-
Interactive visualizations
The dashboard shows real-time metrics and interactive visualizations for 100 security incidents.
Color-coded donut chart showing breakdown of Critical (Red), High (Orange), Medium (Yellow), and Low (Green) severity incidents.
30-day trend analysis showing incident volume over time.
💡 Note: The full interactive dashboard runs locally. During interviews, I can screen share the live version with hover interactions, zoom capabilities, and real-time filtering.
## 🚀 Quick Start
```bash
# Install dependencies
pip3 install pandas plotly
# Run the pipeline
python3 extract_incidents.py
python3 transform_load.py
python3 make_dashboard.py
# Open dashboard
open outputs/dashboard.html
Technical:
- Python programming
- SQL database design (SQLite)
- ETL pipeline development
- Data visualization (Plotly)
- pandas data analysis
Project Management:
- Project planning & scope definition
- Risk management
- Stakeholder communication
- Technical-to-business translation
- Agile methodology
Business Intelligence:
- Dashboard design
- KPI identification
- Data storytelling
- Executive reporting
- TRANSLATION_GUIDE.md - How PM bridges technical and business teams (READ THIS!)
- PROJECT_CHARTER.md - Project scope, ROI, stakeholders
- outputs/dashboard.html - The interactive dashboard
This project taught me:
- ETL pipeline architecture
- Database design and SQL queries
- Creating professional visualizations
- PM documentation best practices
- How to communicate technical work to non-technical audiences
Most candidates say "I have PM experience." This project proves it with:
- Working code
- Professional documentation
- Clear business value
- Execution proof
- Real-time data streaming
- Machine learning for incident prediction
- Additional chart types
- Integration with production SIEM
Built as a portfolio demonstration of PM + Technical capabilities
SudoChef | sudochef.me