kaleabb266/Ethiopian-MedicalData-Warehouse

# Ethiopian Medical Data Warehouse This project builds a **data warehouse** to centralize and analyze Ethiopian medical business data scraped from Telegram channels and web sources. The system integrates **Telegram scraping**, **object detection using YOLO**, **ETL/ELT workflows**, and **FastAPI** for API development. It also includes an **interactive Streamlit dashboard** for real-time monitoring and reporting. --- ## Table of Contents 1. Overview 2. Features 3. Technologies Used 4. Project Structure 5. Getting Started * Prerequisites * Installation 6. Usage * Running the Telegram Scraper * Data Cleaning and Transformation * Object Detection with YOLO * Launching the Streamlit Dashboard * Using the FastAPI Endpoint 7. Contributing 8. License 9. Acknowledgments --- ## Overview The **Ethiopian Medical Data Warehouse** is designed to streamline the collection, storage, and analysis of data related to Ethiopian medical businesses. By leveraging modern data engineering tools and techniques, this project enables: * Centralized storage of structured data in a PostgreSQL database. * Automated scraping of Telegram channels and web sources. * Object detection in images using YOLO for enriched data. * Real-time insights via an interactive Streamlit dashboard. * Seamless integration with downstream applications through a FastAPI endpoint. This solution is particularly valuable for stakeholders in the healthcare and finance sectors, as it helps identify trends, optimize inventory management, and improve decision-making. --- ## Features * **Telegram Scraping**: Extracts data from public Telegram channels relevant to Ethiopian medical businesses. * **Data Cleaning and Transformation**: Uses DBT (Data Build Tool) for ETL/ELT workflows to clean and transform data. * **Object Detection**: Integrates YOLOv5 for detecting objects in images collected from Telegram channels. * **Data Warehouse**: Stores structured data in a scalable PostgreSQL database. * **Intera …