Scenario: Disk IO, CPU, and memory usage must be monitored for SALESDB
The sys.resource_stats returns historical data for CPU, IO, DTU consumption. There's one row every 5 minute for a database in an Azure logical SQL Server if there's a change in the metrics.
Incorrect Answers:
B: Query Performance Insight helps you to quickly identify what your longest running queries are, how they change over time, and what waits are affecting them.
C: sys.dm_os_wait_stats: specific types of wait times during query execution can indicate bottlenecks or stall points within the query. Similarly, high wait times, or wait counts server wide can indicate bottlenecks or hot spots in interaction query interactions within the server instance. For example, lock waits indicate data contention by queries; page IO latch waits indicate slow IO response times; page latch update waits indicate incorrect file layout.
References:
https://dataplatformlabs.com/monitoring-azure-sql-database-with-sys-resource_stats/

The Integration Runtime is a customer managed data integration infrastructure used by Azure Data Factory to provide data integration capabilities across different network environments.
A linked service defines the information needed for Azure Data Factory to connect to a data resource. We have three resources in this scenario for which linked services are needed:
* On-premises SQL Server
* Azure Blob Storage
* Azure SQL database
Note: Azure Data Factory is a fully managed cloud-based data integration service that orchestrates and automates the movement and transformation of data. The key concept in the ADF model is pipeline. A pipeline is a logical grouping of Activities, each of which defines the actions to perform on the data contained in Datasets. Linked services are used to define the information needed for Data Factory to connect to the data resources.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/move-sql-azure-adf

Reference:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-always-encrypted

Reference:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-always-encrypted

See the explanation below.
Explanation
Step 1: Create a new Azure Data Factory V2
1. Go to the Azure portal.
2. Select Create a resource on the left menu, select Analytics, and then select Data Factory.

4. On the New data factory page, enter a name.
5. For Subscription, select your Azure subscription in which you want to create the data factory.
6. For Resource Group, use one of the following steps:
Select Use existing, and select an existing resource group from the list.
Select Create new, and enter the name of a resource group.
7. For Version, select V2.
8. For Location, select the location for the data factory.
9. Select Create.
10. After the creation is complete, you see the Data Factory page.
Step 2: Create a schedule trigger for the Data Factory
1. Select the Data Factory you created, and switch to the Edit tab.

2. Click Trigger on the menu, and click New/Edit.

3. In the Add Triggers page, click Choose trigger..., and click New.

4. In the New Trigger page, do the following steps:
a. Confirm that Schedule is selected for Type.
b. Specify the start datetime of the trigger for Start Date (UTC) to: 24:00:00 c. Specify Recurrence for the trigger. Select Every Hour, and enter 2 in the text box.

5. In the New Trigger window, check the Activated option, and click Next.
6. In the New Trigger page, review the warning message, and click Finish.
7. Click Publish to publish changes to Data Factory. Until you publish changes to Data Factory, the trigger does not start triggering the pipeline runs.

References:
https://docs.microsoft.com/en-us/azure/data-factory/quickstart-create-data-factory-portal
https://docs.microsoft.com/en-us/azure/data-factory/how-to-create-schedule-trigger