DP-300 Exam Dumps - Administering Relational Databases on Microsoft Azure

Step 1: On the master database, run CREATE LOGIN [App1] WITH PASSWORD = ' p@aaW0rd! '

Logins are server wide login and password pairs, where the login has the same password across all databases. Here is some sample Transact-SQL that creates a login:

CREATE LOGIN readonlylogin WITH password= ' 1231!#ASDF!a ' ;

You must be connected to the master database on SQL Azure with the administrative login (which you get from the SQL Azure portal) to execute the CREATE LOGIN command.

Step 2: On DatabaseA, run CREATE USER [App1] FROM LOGIN [App1]

Users are created per database and are associated with logins. You must be connected to the database in where you want to create the user. In most cases, this is not the master database. Here is some sample Transact-SQL that creates a user:

CREATE USER readonlyuser FROM LOGIN readonlylogin;

Step 3: On DatabaseA run ALTER ROLE db_datareader ADD Member [App1]

Just creating the user does not give them permissions to the database. You have to grant them access. In the Transact-SQL example below the readonlyuser is given read only permissions to the database via the db_datareader role.

EXEC sp_addrolemember ' db_datareader ' , ' readonlyuser ' ;

Basic Concept: This question tests choosing the correct Azure migration approach by matching the source platform, target service, downtime tolerance, and administrative effort.

Why A is Correct: Hyperscale matches the expected DP-300 administration action. Hyperscale is designed for very large databases and fast scale-out storage architecture, not merely for intermittent CPU bursts. The question is not asking for a general Azure capability; it is asking for the feature that produces this result: You need to recommend a hosting solution for DB1.

Why B is Wrong: Business Critical provides low-latency local SSD storage and high availability for demanding workloads, but it is usually more expensive than necessary for bursty idle workloads. It applies to a different Azure data-platform design than the one the question is testing.

Why C is Wrong: General Purpose is an Azure data-platform feature, but it must match the workload model, service tier, migration path, or deployment constraint described in the scenario. It would solve a neighboring problem, but not the deployment, sizing, or migration requirement in this item.

Use the Query Store Page in SQL Server Management Studio.

Query performance regressions caused by execution plan changes can be non-trivial and time consuming to resolve.

Since the Query Store retains multiple execution plans per query, it can enforce policies to direct the Query Processor to use a specific execution plan for a query. This is referred to as plan forcing. Plan forcing in Query Store is provided by using a mechanism similar to the USE PLAN query hint, but it does not require any change in user applications. Plan forcing can resolve a query performance regression caused by a plan change in a very short period of time.

Basic Concept: This question tests secure database administration, where the control must match the data state, access boundary, identity model, or compliance requirement.

Why the selected answer is Correct: The selected values fit this scenario because they apply the required Azure SQL configuration at the correct scope and sequence: RG1 contains an instance of SQL Server on Azure Virtual Machines named SQL You need to use PowerShell to enable and configure automated patching for SQL The solution must include both SQL Server and Windows security updates.

Why the alternate choices are Wrong: The alternate selections apply to different administrative stages or different scopes. In a hotspot or drag-drop task, order and scope are part of the answer, so a technically valid Azure feature can still be wrong if it is placed in the wrong step.

Basic Concept: This question tests Azure SQL sizing and purchasing choices, where compute model, scaling behavior, licensing benefits, and cost pattern must be evaluated together.

Why the selected answer is Correct: The selected values fit this scenario because they apply the required Azure SQL configuration at the correct scope and sequence: You need to deploy two virtual machines named VM1 and VM2 that will host Microsoft SQL Server instances.

Why the alternate choices are Wrong: The alternate selections apply to different administrative stages or different scopes. In a hotspot or drag-drop task, order and scope are part of the answer, so a technically valid Azure feature can still be wrong if it is placed in the wrong step.

The REPLACE option overrides several important safety checks that restore normally performs. The overridden checks are as follows:

Restoring over an existing database with a backup taken of another database.

With the REPLACE option, restore allows you to overwrite an existing database with whatever database is in the backup set, even if the specified database name differs from the database name recorded in the backup set. This can result in accidentally overwriting a database by a different database.

Step 1: Set up the Active Directory Admin for AzSQL1.

Step 2: Connect to DB1 by using the server administrator.

Sign into your managed instance with an Azure AD login granted with the sysadmin role.

Step 3: Create a user by using the FROM EXTERNAL PROVIDER clause.

FROM EXTERNAL PROVIDER is available for creating server-level Azure AD logins in SQL Database managed instance. Azure AD logins allow database-level Azure AD principals to be mapped to server-level Azure AD logins. To create an Azure AD user from an Azure AD login use the following syntax:

CREATE USER [AAD_principal] FROM LOGIN [Azure AD login]

Serverless SQL pool can automatically synchronize metadata from Apache Spark. A serverless SQL pool database will be created for each database existing in serverless Apache Spark pools.

For each Spark external table based on Parquet and located in Azure Storage, an external table is created in a serverless SQL pool database. As such, you can shut down your Spark pools and still query Spark external tables from serverless SQL pool.