ETL-Episode_III

This repository contains the necessary materials for learning Transform and Load (ETL) processes. It includes code examples, exercises, and images.

Folder Structure and Usage

• 1-Data_Transformation_Storage.ipynb: the notebook provides examples of data transformation and storage using ETL techniques. Content Resources.
• 2-Exercises.ipynb: the notebook contains exercises for practicing ETL concepts.
• Images: Contains images used in the notebooks.

Feel free to explore the notebooks, modify the code, and experiment with different techniques to enhance your learning experience! Don't hesitate to try out different scenarios, test different transformations, or come up with your own creative solutions. The best way to learn is by hands-on practice and experimentation. Don't be afraid to make mistakes and learn from them. Enjoy the process of exploring and discovering new possibilities with ETL!

Getting Started

To get started with the examples and exercises, follow these steps:

1. Clone the repository to your local machine.
2. Ensure you have Jupyter Notebook installed.
3. Open the Jupyter Notebook server.
4. Navigate to the repository folder.
5. Open the notebook files (*.ipynb) to explore the code examples and exercises.

Usage

• The 1-Data_Transformation_Storage.ipynb notebook provides examples of data transformation and storage using ETL techniques.
• The 2-Exercises.ipynb notebook contains exercises for practicing ETL concepts.

Solutions

Solutions can be found in the 'solutions' branch.

Contributors

If you find any issues or have suggestions for improvement, please create an issue or submit a pull request.