Explanation
Graphical user interface, text, application, email Description automatically generated

Box 1: Install a self-hosted integration runtime
The Integration Runtime is a customer-managed data integration infrastructure used by Azure Data Factory to provide data integration capabilities across different network environments.
Box 2: Create a pipeline
With ADF, existing data processing services can be composed into data pipelines that are highly available and managed in the cloud. These data pipelines can be scheduled to ingest, prepare, transform, analyze, and publish data, and ADF manages and orchestrates the complex data and processing dependencies References:
https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/move-sql-azure-adf
https://docs.microsoft.com/pl-pl/azure/data-factory/tutorial-hybrid-copy-data-tool syu31svc 3 months, 4 weeks ago
https://docs.microsoft.com/en-us/azure/data-factory/create-self-hosted-integration-runtime?tabs=data-factory
"A self-hosted integration runtime can run copy activities between a cloud data store and a data store in a private network"
https://docs.microsoft.com/en-us/azure/data-factory/introduction
"With Data Factory, you can use the Copy Activity in a data pipeline to move data from both on-premises and cloud source data stores to a centralization data store in the cloud for further analysis"

Explanation
Graphical user interface, table Description automatically generated

Allowed authentication methods: GET only
Authorization level: Anonymous
The option is Allow Anonymous requests. This option turns on authentication and authorization in App Service, but defers authorization decisions to your application code. For authenticated requests, App Service also passes along authentication information in the HTTP headers.
This option provides more flexibility in handling anonymous requests.
References:
https://docs.microsoft.com/en-us/azure/app-service/overview-authentication-authorization

Explanation
Microsoft recommends that you use a GPv2 storage account for most scenarios. It supports up to 5 PB, and blob storage including Data Lake storage.
Note: A key mechanism that allows Azure Data Lake Storage Gen2 to provide file system performance at object storage scale and prices is the addition of a hierarchical namespace. This allows the collection of objects/files within an account to be organized into a hierarchy of directories and nested subdirectories in the same way that the file system on your computer is organized. With a hierarchical namespace enabled, a storage account becomes capable of providing the scalability and cost-effectiveness of object storage, with file system semantics that are familiar to analytics engines and frameworks.
References:
https://docs.microsoft.com/en-us/azure/storage/common/storage-account-overview
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-namespace