I presented this session at Power Break on March 22, 2021. Topics coevered - limitations of using Python query in Power BI, importance of MLOps, deploying ML models in Azure ML and consuming them in Power BI
Power BI and Azure ML have native integration with each other, which means not only that you can consume the deployed models in Power BI but also use the resources/tools in Azure ML to manage the model lifecycle. There is a misconception that you need Power BI Premium to use Azure ML. In this session I show that's not the case. Below are the topics covered:
Limitation of using Python or R in Power BI
Steps to access Azure ML models in Power BI
Invoking Azure ML models in Power Query in Desktop and using dataflow in service
Thoughts on batch-scoring
Other considerations:
youtube: https://youtu.be/oLdMFJIxWDo
References:
https://docs.microsoft.com/en-us/power-bi/connect-data/service-aml-integrate
https://pawarbi.github.io/blog/powerbi/r/python/2020/05/15/powerbi-python-r-tips.html
https://docs.microsoft.com/en-us/power-bi/connect-data/desktop-python-scripts
https://docs.microsoft.com/en-us/azure/machine-learning/tutorial-power-bi-custom-model