Want to use notebooks to leverage data from a Power BI semantic model (dataset)? Maybe you’re a data scientist wanting to augment your models with that data, or maybe you just want to validate stuff as a Power BI developer. Semantic Link (or Sempy) can help!

Sample Notebook: https://github.com/guyinacube/demo-files/blob/master/video%20demos/Synapse/20231019%20-%20Sempy.ipynb

What is semantic link?
https://learn.microsoft.com/fabric/data-science/semantic-link-overview

Tutorial: Clean data with functional dependencies
https://learn.microsoft.com/fabric/data-science/tutorial-data-cleaning-functional-dependencies

Tutorial: Extract and calculate Power BI measures from a Jupyter notebook
https://learn.microsoft.com/fabric/data-science/tutorial-power-bi-measures

Detect, explore, and validate functional dependencies in your data
https://learn.microsoft.com/fabric/data-science/semantic-link-validate-data

fabric Package
https://learn.microsoft.com/python/api/semantic-link-sempy/sempy.fabric?view=semantic-link-python

📢 Become a member: https://guyinacu.be/membership

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Want to take your Power BI skills to the next level? We have training courses available to help you with your journey.

🎓 Guy in a Cube courses: https://guyinacu.be/courses

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