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https://github.com/dantesbytes/electrical-grid-data

full-stack web application that provides real-time monitoring and analysis from data generated by electrical grids .
https://github.com/dantesbytes/electrical-grid-data

dataengineering docker fastapi jupyter-notebook machine-learning pyspark python terraform

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full-stack web application that provides real-time monitoring and analysis from data generated by electrical grids .

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# Brillant Labs Demo

# And Another One

# Electrical Grid Stability Dashboard

## Project Overview

This project is a full-stack web application that provides real-time monitoring and analysis from data generated by electrical grids . It utilizes machine learning to predict potential failures and a notification system to alert users about critical issues.

### Key Features

- Real-time dashboard visualizing grid metrics
- Predictive analytics for failure rates
- Notification system for critical alerts
- Historical data analysis and reporting

## Tech Stack

### Backend
- Python 3.8+
- FastAPI: High-performance web framework
- PySpark: Distributed data processing
- Pandas: Data manipulation and analysis
- Scikit-learn: Machine learning for predictive analytics
- APScheduler: Task scheduling
- Celery: Asynchronous task queue for notifications

### Frontend
- React: UI framework
- D3.js: Data visualization library
- Axios: HTTP client for API requests

### Database
- PostgreSQL: Persistent data storage
- Redis: Caching and message broker

### DevOps
- Docker & Docker Compose: Containerization and orchestration
- Nginx: Reverse proxy server
- Gunicorn: WSGI HTTP Server

### Monitoring
- Prometheus & Grafana: Application monitoring
- ELK Stack: Centralized logging