#################################
3. HOOPS AI - Minimal ETL Demo
#################################

This notebook demonstrates the core features of the HOOPS AI data engineering workflows:

Key Components

   - **Schema-Based Dataset Organization**: Define structured data schemas for consistent data merging
   - **Parallel Task Decorators**: Simplify CAD processing with type-safe task definitions
   - **Generic Flow Orchestration**: Automatically handle task dependencies and data flow
   - **Automatic Dataset Merging**: Process multiple files into a unified dataset structure
   - **Integrated Exploration Tools**: Analyze and prepare data for ML workflows

Run the notebook within the ``hoops_ai_cpu`` environment outlined in :doc:`/getting_started/evaluate`.

The code and resources for this tutorial can be found in the `HOOPS-AI-Tutorials <https://github.com/techsoft3d/HOOPS-AI-tutorials/tree/main>`__ Github repository.

.. hint::
   Launch ``jupyter lab notebooks/3a_ETL_pipeline_using_flow.ipynb`` from the bundle root to experiment with the sample workflow.

.. toctree::
   :maxdepth: 1
   :titlesonly:

   /tutorials/hoops_ai_tutorials/notebooks/3a_ETL_pipeline_using_flow.ipynb