Merge pull request #180599 from nibaccam/limit-cred-automl

AutoML | limits for id based data acces

Author: PRMerger19

articles/machine-learning/how-to-configure-auto-train.md

@@ -58,6 +58,9 @@ Requirements for training data in machine learning:
 - Data must be in tabular form.
 - The value to predict, target column, must be in the data.
 
+> [!IMPORTANT]
+> Automated ML experiments do not support training with datasets that use [identity-based data access](how-to-identity-based-data-access.md).
+
 **For remote experiments**, training data must be accessible from the remote compute. Automated ML only accepts [Azure Machine Learning TabularDatasets](/python/api/azureml-core/azureml.data.tabulardataset) when working on a remote compute. 
 
 Azure Machine Learning datasets expose functionality to:

articles/machine-learning/how-to-identity-based-data-access.md

@@ -155,10 +155,12 @@ sqldb_dstore = Datastore.register_azure_sql_database(workspace=ws,
 
 ## Use data in storage
 
-We recommend that you use [Azure Machine Learning datasets](how-to-create-register-datasets.md) when you interact with your data in storage with Azure Machine Learning. 
+We recommend that you use [Azure Machine Learning datasets](how-to-create-register-datasets.md) when you interact with your data in storage with Azure Machine Learning.  
 
-Datasets package your data into a lazily evaluated consumable object for machine learning tasks like training. Also, with datasets you can [download or mount](how-to-train-with-datasets.md#mount-vs-download) files of any format from Azure storage services like Azure Blob Storage and Azure Data Lake Storage to a compute target.
+> [!IMPORTANT]
+> Datasets using identity-based data access is not supported for [automated ML experiments](how-to-configure-auto-train.md).
 
+Datasets package your data into a lazily evaluated consumable object for machine learning tasks like training. Also, with datasets you can [download or mount](how-to-train-with-datasets.md#mount-vs-download) files of any format from Azure storage services like Azure Blob Storage and Azure Data Lake Storage to a compute target.
 
 To create datasets with identity-based data access, you have the following options. This type of dataset creation uses your Azure Active Directory token for data access authentication.