PythonETLPipelineProjects 📊

Welcome to PythonETLPipelineProjects! This repository showcases my Python projects and DataCamp course progress on ETL/ELT data pipelines and data warehousing. It’s a practical resource for:

• Aspiring data engineers 🚀
• Developers seeking Python data pipeline examples 🐍
• Learners interested in data warehousing 📚

Contents 📋

• Courses:
  • ETL and ELT in Python 🎓
  • Data Warehousing Concepts 🎓
• Project:
  • Data Pipeline ETL with Python 🛠️

Courses Completed 📚

ETL and ELT in Python 🎓

• Built performant data pipelines using Python libraries (e.g., pandas, json).
• Covered extraction from structured/unstructured sources, transformation techniques, and loading data.
• Explored pipeline validation, unit testing, and monitoring.

Data Warehousing Concepts 🎓

• Studied data warehouses, data marts, and data lakes.
• Compared Inmon’s top-down and Kimball’s bottom-up approaches.
• Mastered Kimball’s data modeling and handling slowly changing dimensions.
• Understood OLAP vs. OLTP systems.

Prerequisites 🛠️

• Python 3.8+
• Libraries: pandas, sqlalchemy, numpy, logging, pytest
• Optional: [Specify tools like PostgreSQL, Airflow, or cloud platforms if used]

Getting Started 🚀

1. Clone the repository:

   git clone https://github.com/[YourUsername]/PythonETLPipelineProjects.git  

2. Install dependencies:

   pip install -r requirements.txt  

3. Run the project:

   python Project1/main.py  

Requires Python 3.8+

License 📄

MIT License - see LICENSE.