Explanation:

Basic Concept: This question tests plan and implement data platform resources in the DP-300 exam context.
The correct choice is determined by the exact service boundary and operational requirement stated in the scenario.
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 have two resource groups named RG1 and RG2.
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 high availability and disaster recovery design for Azure SQL, SQL Server on Azure VMs, and regional failure scenarios.
Why B is Correct: 35 days is part of the availability or recovery design space, but the correct choice must satisfy the specified failover, restore, quorum, RPO, or RTO requirement. In this scenario, the important constraint is: You need to enable point-in-time recovery (PITR) backups for DBl. 35 days satisfies that constraint without adding an unrelated service or manual process.
Why A is Wrong: seven days is part of the availability or recovery design space, but the correct choice must satisfy the specified failover, restore, quorum, RPO, or RTO requirement. It is not wrong technology in general, but it is the wrong HA/DR control for this scenario ' s failure model.
Why C is Wrong: 180 days is part of the availability or recovery design space, but the correct choice must satisfy the specified failover, restore, quorum, RPO, or RTO requirement. It handles a different resilience pattern and would not deliver the failover or recovery behavior required here.
Why D is Wrong: 365 days is part of the availability or recovery design space, but the correct choice must satisfy the specified failover, restore, quorum, RPO, or RTO requirement. It is not wrong technology in general, but it is the wrong HA/DR control for this scenario ' s failure model.

See the explanation part for the complete Solution.
Explanation:
Connect to db1 in SQL Server Management Studio and run:
ALTER DATABASE [db1]
SET QUERY_STORE (MAX_STORAGE_SIZE_MB = 4000);
Microsoft documents that Query Store maximum storage size is changed with:
ALTER DATABASE < database_name >
SET QUERY_STORE (MAX_STORAGE_SIZE_MB = < size > );
For Azure SQL Database, the maximum allowed MAX_STORAGE_SIZE_MB value is 10,240 MB, so 4,000 MB is valid.
Method 1 - SSMS / T-SQL Method
This is the cleanest method for the simulation.
Step 1: Open SQL Server Management Studio
Open SQL Server Management Studio.
Connect to the Azure SQL logical server that hosts db1.
Use SQL authentication or Microsoft Entra authentication.
In Connection Properties, select:
db1
You can also connect to master, but for this task it is cleaner to open a query window in db1.
Step 2: Run the Query Store configuration command
Open a new query window and run:
ALTER DATABASE [db1]
SET QUERY_STORE (MAX_STORAGE_SIZE_MB = 4000);
This changes the Query Store maximum allocated storage size to 4,000 MB.
Step 3: Verify the setting
Run this query in db1:
SELECT
actual_state_desc,
desired_state_desc,
current_storage_size_mb,
max_storage_size_mb
FROM sys.database_query_store_options;
Expected result:
max_storage_size_mb = 4000
Microsoft documents sys.database_query_store_options as the catalog view that returns Query Store configuration, including max_storage_size_mb.
Method 2 - SSMS Graphical Method
Use this if the simulation expects a GUI action.
Step 1: Connect to the server
Open SQL Server Management Studio.
Connect to the Azure SQL logical server.
Expand Databases.
Right-click db1.
Select Properties.
Step 2: Open Query Store settings
In the Database Properties window, select Query Store.
Find the setting:
Max Size (MB)
or:
Maximum Storage Size (MB)
Change the value to:
4000
Select OK.
Step 3: Verify
Run:
SELECT max_storage_size_mb
FROM sys.database_query_store_options;
Expected value:
4000
Azure Portal Clarification
The Azure portal is not the best tool for this specific Query Store configuration. Query Store size is a database engine setting, not a normal Azure resource setting like backup retention, locks, alerts, or private endpoints.
Use SSMS/T-SQL for this task.
Important Notes
Query Store must remain enabled
Do not disable Query Store. Azure SQL Database uses Query Store heavily, and Microsoft notes that Query Store is enabled by default for Azure SQL Database. The task only asks to increase the maximum storage size, not to change capture mode, cleanup policy, or operation mode.
4,000 MB is valid
Azure SQL Database allows Query Store MAX_STORAGE_SIZE_MB up to 10,240 MB, so this setting is within the allowed range.
Final Exam-Lab Action
Run this against db1:
ALTER DATABASE [db1]
SET QUERY_STORE (MAX_STORAGE_SIZE_MB = 4000);
Then verify with:
SELECT max_storage_size_mb
FROM sys.database_query_store_options;
The task is complete when the result shows:
4000

Basic Concept: This question tests performance optimization for SQL workloads, including Query Store, automatic tuning, index/statistics maintenance, and engine-level resource behavior.
Why D is Correct: Option D is related to operational monitoring or tuning, but it must match the exact signal needed: query history, resource utilization, wait/blocking detail, or automatic remediation. This fits the case because the requested outcome is: You need to identify the operations that are being performed on the index.
The selected feature addresses that outcome directly rather than relying on a workaround.
Why A is Wrong: Option A is related to operational monitoring or tuning, but it must match the exact signal needed: query history, resource utilization, wait/blocking detail, or automatic remediation. It does not expose the required metric, query history, wait/blocking signal, or tuning mechanism; using it would not give the administrator the evidence requested.
Why B is Wrong: Option B is related to operational monitoring or tuning, but it must match the exact signal needed: query history, resource utilization, wait/blocking detail, or automatic remediation. It is useful in other troubleshooting paths, but this scenario requires a more specific monitoring or optimization feature.
Why C is Wrong: Option C is related to operational monitoring or tuning, but it must match the exact signal needed: query history, resource utilization, wait/blocking detail, or automatic remediation. It would produce a different operational signal than the one needed to investigate, alert, or tune the workload in this question.

Basic Concept: This question tests database auditing and query visibility. DP-300 expects you to distinguish between collecting audit events, retaining logs, and analyzing query behavior.
Why A is Correct: Apply a sensitivity label to each column. is correct because it is the feature whose normal purpose matches the stated requirement. Apply a sensitivity label to each column. is a security-related control, but its value depends on whether the requirement is identity, encryption, auditing, network isolation, or data exposure reduction. The scenario wording points to that specific behavior: You need to recommend a data classification strategy for Customers.
Why B is Wrong: Transparent Data Encryption protects database files, backups, and logs at rest; it does not encrypt data in use or enforce user-level data visibility. It does not satisfy the required identity, encryption, firewall, auditing, or data-exposure boundary described in the scenario: You need to recommend a data classification strategy for Customers.
Why C is Wrong: Dynamic Data Masking obscures sensitive values in query results for non-privileged users, but it does not restrict which rows are returned. It protects or manages a different security layer, so the required database access or protection behavior would still be incomplete.
Why D is Wrong: Apply a sensitivity label to Customers is a security-related control, but its value depends on whether the requirement is identity, encryption, auditing, network isolation, or data exposure reduction. It is not the right enforcement point for this case; the scenario needs the control that governs the data or identity path being tested.