An end-to-end data pipeline for scraping, transforming, enriching, and serving Ethiopian medical business data from public Telegram channels, using a modern ELT data warehouse architecture with dbt, YOLOv8, Dagster, and FastAPI.
# 10 Academy: Artificial Intelligence Mastery - Week 7 Challenge
## Project: Building a Data Warehouse for Ethiopian Medical Business Data
**Date:** July 09 - july 15, 2025
**Overview:**
This project focuses on building a data warehouse to store and analyze data related to Ethiopian medical businesses scraped from Telegram channels. The goal is to develop a robust, scalable solution that incorporates data scraping, cleaning, transformation, object detection using YOLO, and data warehousing best practices. This project also exposes the collect data through a fast API
**Business Need:**
Kara Solutions, a leading data science company, requires a data warehouse to centralize and analyze data on Ethiopian medical businesses. This will enable comprehensive analysis, identification of trends, and improved decision-making for their clients.
**Core Tasks:**
1. **Data Scraping and Collection Pipeline:** Extract data from relevant Telegram channels.
2. **Data Cleaning and Transformation Pipeline:** Clean and transform the scraped data for analysis.
3. **Object Detection using YOLO:** Integrate YOLO for object detection in images scraped from Telegram channels.
4. **Data Warehouse Design and Implementation:** Design and implement a data warehouse to store the processed data.
5. **Data Integration and Enrichment:** Integrate and enrich the data within the data warehouse.
6. **Expose the collect data using Fast API.**
## Deliverables:
### Task 1: Data Scraping and Collection Pipeline
**Objective:** Extract data from Telegram channels and store it for further processing.
**Steps:**
1. **Telegram Scraping:**
- Utilize the Telegram API (e.g., via `telethon`) or custom scripts to extract data from public Telegram channels relevant to Ethiopian medical businesses.
- **Example Channels:**
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t.me
- Chemed Telegram Channel (Link needed. Assumed to be a channel named "Chemed")
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t.me
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t.me
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t.me …