You create an Azure Machine Learning workspace. The workspace contains a dataset named sample_dataset, a compute instance, and a compute cluster.
You must create a two-stage pipeline that will prepare data in the dataset and then train and register a model based on the prepared data.
The first stage of the pipeline contains the following code:

You need to identify the location containing the output of the first stage of the script that you can use as input for the second stage.
Which storage location should you use?
Correct Answer: A
When you create a workspace, an Azure blob container and an Azure file share are automatically registered as datastores to the workspace. They're named workspaceblobstore and workspacefilestore, respectively. The workspaceblobstore is used to store workspace artifacts and your machine learning experiment logs. It's also set as the default datastore and can't be deleted from the workspace. The workspacefilestore is used to store notebooks and R scripts authorized via compute instance.
https://learn.microsoft.com/en-us/azure/machine-learning/v1/how-to-access-data