Storing and retrieving data in Azure Machine Learning

The first task is storing and retrieving data in Azure Machine Learning. You can bring data into Machine Learning in a multitude of ways. That includes anything from your local machine, a source on the internet, or even cloud-based storage. In this section, we will explore all those concepts.

Let us see how to work with datastores.

Connecting datastores

As we mentioned in the Azure Machine Learning introduction in Chapter 1, datastores serve as a reference to an existing storage service, whether that is a storage account or a database. If you already have a reference or a connection to your data, this is not mandatory, as you can connect external sources as well, but connecting datastores has many benefits. Firstly, you have a common way to connect different data sources to your workspace without the need to add credential information anywhere in your scripts or your code, which is a best practice in terms of security....