jodahe1/Kara-Solutions

This repository contains the code and documentation for the Kara Solutions Data Warehouse project. The goal of this project is to build a robust and scalable data warehouse to store data on Ethiopian medical businesses, which has been scraped from the web and Telegram channels. # Kara Solutions Data Warehouse This repository contains the code and documentation for the Kara Solutions Data Warehouse project. The goal of this project is to build a robust and scalable data warehouse to store data on Ethiopian medical businesses, which has been scraped from the web and Telegram channels. ## Table of Contents - Introduction - Features - Technologies Used - Installation - Usage - Contributing - License ## Introduction The Kara Solutions Data Warehouse project aims to provide a comprehensive and scalable solution for storing and analyzing data related to Ethiopian medical businesses. This data is collected from various sources including web scraping and Telegram channels. ## Features - **Data Collection**: Automated scripts for web scraping and collecting data from Telegram channels. - **Data Storage**: A scalable data warehouse to efficiently store large volumes of data. - **Data Analysis**: Tools and scripts for analyzing the collected data. - **Reporting**: Generation of detailed reports based on the analysis of the data. ## Technologies Used - **Python**: For web scraping and data processing. - **SQL**: For managing the data warehouse. - **ETL Tools**: For extracting, transforming, and loading data. - **Data Visualization Tools**: For creating reports and visualizations. ## Installation To set up the project locally, follow these steps: 1. Clone the repository: ```bash git clone github.com ``` 2. Navigate to the project directory: ```bash cd Kara-Solutions ``` 3. Install the required dependencies: ```bash pip install -r requirements.txt ``` ## Usage 1. To start the data collection process, run the web scraping and Telegram data collection scripts: ```bash python scrape_web.py python scrape_telegram.py ``` 2. Load the collected data into the data warehouse: ```bash python load_data.py ``` 3. Run data analysis scripts to generate reports: ```bash python analyze_data.py ``` ## Contributing Contributions …