If you’re using your own organizational Azure Data Lake Storage Gen2 account for Power BI dataflows, you can use the CDM folders that Power BI creates as a data source for other efforts, including data science with tools like Azure Machine Learning and Azure Databricks.
This capability has been in preview since early this year, so it’s not really new, but there are enough pieces involved that it may not be obvious how to begin – and I continue to see enough questions about this topic that another blog post seemed warranted.
The key point is that because dataflows are writing data to ADLSg2 in CDM folder format, Azure Machine Learning and Azure Databricks can both read the data using the metadata in the model.json file.
This json file serves as the “endpoint” for the data in the CDM folder; it’s a single resource that you can connect to, and not have to worry about the complexities in the various subfolders and files that the CDM folder contains.
This tutorial is probably the best place to start if you want to know more. It includes directions and sample code for creating and consuming CDM folders from a variety of different Azure services – and Power BI dataflows. If you’re one of the people who has recently asked about this, please go through this tutorial as your next step!
 It’s the best resource I’m aware of – if you find a better one, please let me know!