Update how-to-access-data.md

First draft to address unsupported data sources and limitations

Author: lebaro-msft

articles/machine-learning/v1/how-to-access-data.md

@@ -68,7 +68,7 @@ For a low code experience, see how to use the [Azure Machine Learning studio to
 Datastores currently support storing connection information to the storage services listed in the following matrix. 
 
 > [!TIP]
-> **For unsupported storage solutions**, and to save data egress cost during ML experiments, [move your data](#move-data-to-supported-azure-storage-solutions) to a supported Azure storage solution. 
+> **For unsupported storage solutions** (those not listed in the table below), you may run into issues connecting and working with this data. [Move your data](#move-data-to-supported-azure-storage-solutions) to a supported Azure storage solution. Doing this may also help with additional scenarios, like saving data egress cost during ML experiments.
 
 | Storage type | Authentication type | [Azure Machine Learning studio](https://ml.azure.com/) | [Azure Machine Learning  Python SDK](/python/api/overview/azure/ml/intro) |  [Azure Machine Learning CLI](reference-azure-machine-learning-cli.md) | [Azure Machine Learning  REST API](/rest/api/azureml/) | VS Code
 ---|---|---|---|---|---|---
@@ -304,4 +304,4 @@ Azure Data Factory provides efficient and resilient data transfer with more than
 
 * [Create an Azure machine learning dataset](how-to-create-register-datasets.md)
 * [Train a model](../how-to-set-up-training-targets.md)
-* [Deploy a model](../how-to-deploy-and-where.md)
+* [Deploy a model](../how-to-deploy-and-where.md)