A comprehensive data warehouse solution for Ethiopian medical business data; integrating Telegram scraping, image object detection using YOLO and ETL/ELT pipelines for efficient data processing and analysis.
# Ethiopian-Medical-Data-Warehouse
A comprehensive data warehouse solution for Ethiopian medical business data, integrating Telegram scraping, image object detection using YOLO, and ETL/ELT pipelines for efficient data processing and analysis.
## Overview
The **Ethiopian Medical Data Warehouse** project aims to build a robust, scalable data warehouse that stores data on Ethiopian medical businesses scraped from the web and Telegram channels. The project integrates advanced data extraction techniques and object detection capabilities using YOLO (You Only Look Once) to enhance data analysis.
This repository will serve as a centralized hub for all project components, including data extraction scripts, ETL/ELT processes, object detection models, and more.
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## Features
- **Data Scraping:** Collect data from public Telegram channels relevant to Ethiopian medical businesses.
- **Object Detection:** Utilize YOLO models for analyzing image data.
- **ETL/ELT Pipelines:** Efficient data transformation and storage strategies.
- **Data Storage:** Organize raw and processed data for analysis.
- **Monitoring and Logging:** Track progress and debug the scraping process.