Data in Azure ML

Datastores

In Azure Machine Learning, datastores are abstractions for cloud data sources. They encapsulate the information required to connect to data sources. You can access datastores directly in code by using the Azure Machine Learning SDK, and use it to upload or download data.

Types of Datastore Azure Machine Learning supports the creation of datastores for multiple kinds of Azure data source, including:

• Azure Storage (blob and file containers)
• Azure Data Lake stores
• Azure SQL Database
• Azure Databricks file system (DBFS)

Passing data between Azure ML steps..

The OutputFileDatasetConfig object is a special kind of dataset that:

• References a location in a datastore for interim storage of data.
• Creates a data dependency between pipeline steps.