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Microsoft DP-300 Exam Questions
Administering Microsoft Azure SQL Solutions (Page 3 )

Updated On: 21-Feb-2026
Page 3 of 85
PDF with 430 Questions

You have a SQL pool in Azure Synapse that contains a table named dbo.Customers. The table contains a column name Email.

You need to prevent nonadministrative users from seeing the full email addresses in the Email column. The users must see values in a format of aXXX@XXXX.com instead.

What should you do?

  1. From the Azure portal, set a mask on the Email column.
  2. From the Azure portal, set a sensitivity classification of Confidential for the Email column.
  3. From Microsoft SQL Server Management Studio, set an email mask on the Email column.
  4. From Microsoft SQL Server Management Studio, grant the SELECT permission to the users for all the columns in the dbo.Customers table except Email.

Answer(s): A



You have an Azure Databricks workspace named workspace1 in the Standard pricing tier. Workspace1 contains an all-purpose cluster named cluster1.

You need to reduce the time it takes for cluster1 to start and scale up. The solution must minimize costs.

What should you do first?

  1. Upgrade workspace1 to the Premium pricing tier.
  2. Configure a global init script for workspace1.
  3. Create a pool in workspace1.
  4. Create a cluster policy in workspace1.

Answer(s): C

Explanation:

You can use Databricks Pools to Speed up your Data Pipelines and Scale Clusters Quickly.
Databricks Pools, a managed cache of virtual machine instances that enables clusters to start and scale 4 times faster.


Reference:

https://databricks.com/blog/2019/11/11/databricks-pools-speed-up-data-pipelines.html



Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You have an Azure Synapse Analytics dedicated SQL pool that contains a table named Table1.

You have files that are ingested and loaded into an Azure Data Lake Storage Gen2 container named container1.

You plan to insert data from the files into Table1 and transform the data. Each row of data in the files will produce one row in the serving layer of Table1.

You need to ensure that when the source data files are loaded to container1, the DateTime is stored as an additional column in Table1.

Solution: In an Azure Synapse Analytics pipeline, you use a Get Metadata activity that retrieves the DateTime of the files.

Does this meet the goal?

  1. Yes
  2. No

Answer(s): A

Explanation:

You can use the Get Metadata activity to retrieve the metadata of any data in Azure Data Factory or a Synapse pipeline. You can use the output from the Get Metadata activity in conditional expressions to perform validation, or consume the metadata in subsequent activities.


Reference:

https://docs.microsoft.com/en-us/azure/data-factory/control-flow-get-metadata-activity



Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You have an Azure Synapse Analytics dedicated SQL pool that contains a table named Table1.

You have files that are ingested and loaded into an Azure Data Lake Storage Gen2 container named container1.

You plan to insert data from the files into Table1 and transform the data. Each row of data in the files will produce one row in the serving layer of Table1.

You need to ensure that when the source data files are loaded to container1, the DateTime is stored as an additional column in Table1.

Solution: You use an Azure Synapse Analytics serverless SQL pool to create an external table that has an additional DateTime column.

Does this meet the goal?

  1. Yes
  2. No

Answer(s): B

Explanation:

This is not about an external table.
Instead, in an Azure Synapse Analytics pipeline, you use a Get Metadata activity that retrieves the DateTime of the files.
Note: You can use the Get Metadata activity to retrieve the metadata of any data in Azure Data Factory or a Synapse pipeline. You can use the output from the Get Metadata activity in conditional expressions to perform validation, or consume the metadata in subsequent activities.


Reference:

https://docs.microsoft.com/en-us/azure/data-factory/control-flow-get-metadata-activity



Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You have an Azure Synapse Analytics dedicated SQL pool that contains a table named Table1.

You have files that are ingested and loaded into an Azure Data Lake Storage Gen2 container named container1.

You plan to insert data from the files into Table1 and transform the data. Each row of data in the files will produce one row in the serving layer of Table1.

You need to ensure that when the source data files are loaded to container1, the DateTime is stored as an additional column in Table1.

Solution: You use a dedicated SQL pool to create an external table that has an additional DateTime column.

Does this meet the goal?

  1. Yes
  2. No

Answer(s): B

Explanation:

Instead, in an Azure Synapse Analytics pipeline, you use a Get Metadata activity that retrieves the DateTime of the files.
Note: You can use the Get Metadata activity to retrieve the metadata of any data in Azure Data Factory or a Synapse pipeline. You can use the output from the Get Metadata activity in conditional expressions to perform validation, or consume the metadata in subsequent activities.


Reference:

https://docs.microsoft.com/en-us/azure/data-factory/control-flow-get-metadata-activity






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