DP-203 Free Practice Test

- (Exam Topic 3)
You have an Azure Synapse Analytics SQL pool named Pool1 on a logical Microsoft SQL server named Server1.
You need to implement Transparent Data Encryption (TDE) on Pool1 by using a custom key named key1. Which five actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Solution:
Graphical user interface, text, application Description automatically generated
Step 1: Assign a managed identity to Server1
You will need an existing Managed Instance as a prerequisite.
Step 2: Create an Azure key vault and grant the managed identity permissions to the vault Create Resource and setup Azure Key Vault.
Step 3: Add key1 to the Azure key vault
The recommended way is to import an existing key from a .pfx file or get an existing key from the vault. Alternatively, generate a new key directly in Azure Key Vault.
Step 4: Configure key1 as the TDE protector for Server1 Provide TDE Protector key
Step 5: Enable TDE on Pool1 Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/managed-instance/scripts/transparent-data-encryption-byok-po

Does this meet the goal?

1. A. Yes
2. B. No

Correct Answer: A

- (Exam Topic 3)
You have a partitioned table in an Azure Synapse Analytics dedicated SQL pool. You need to design queries to maximize the benefits of partition elimination. What should you include in the Transact-SQL queries?

1. A. JOIN
2. B. WHERE
3. C. DISTINCT
4. D. GROUP BY

Correct Answer: B

- (Exam Topic 3)
You have an Azure Data Factory pipeline named pipeline1 that is invoked by a tumbling window trigger named Trigger1. Trigger1 has a recurrence of 60 minutes.
You need to ensure that pipeline1 will execute only if the previous execution completes successfully. How should you configure the self-dependency for Trigger1?

1. A. offset: "-00:01:00" size: "00:01:00"
2. B. offset: "01:00:00" size: "-01:00:00"
3. C. offset: "01:00:00" size: "01:00:00"
4. D. offset: "-01:00:00" size: "01:00:00"

Correct Answer: D
Tumbling window self-dependency properties
In scenarios where the trigger shouldn't proceed to the next window until the preceding window is successfully completed, build a self-dependency. A self-dependency trigger that's dependent on the success of earlier runs of itself within the preceding hour will have the properties indicated in the following code.
Example code:
"name": "DemoSelfDependency", "properties": {
"runtimeState": "Started", "pipeline": { "pipelineReference": { "referenceName": "Demo", "type": "PipelineReference"
}
},
"type": "TumblingWindowTrigger", "typeProperties": {
"frequency": "Hour", "interval": 1,
"startTime": "2018-10-04T00:00:00Z", "delay": "00:01:00",
"maxConcurrency": 50, "retryPolicy": { "intervalInSeconds": 30
},
"dependsOn": [
{
"type": "SelfDependencyTumblingWindowTriggerReference",
"size": "01:00:00",
"offset": "-01:00:00"
}
]
}
}
}
Reference: https://docs.microsoft.com/en-us/azure/data-factory/tumbling-window-trigger-dependency

- (Exam Topic 3)
You are designing a security model for an Azure Synapse Analytics dedicated SQL pool that will support multiple companies. You need to ensure that users from each company can view only the data of their
respective company. Which two objects should you include in the solution? Each correct answer presents part of the solution
NOTE: Each correct selection it worth one point.

1. A. a custom role-based access control (RBAC) role.
2. B. asymmetric keys
3. C. a predicate function
4. D. a column encryption key
5. E. a security policy

Correct Answer: AE
Reference:
https://docs.microsoft.com/en-us/sql/relational-databases/security/row-level-security https://docs.microsoft.com/en-us/azure/synapse-analytics/security/synapse-workspace-access-control-overview

- (Exam Topic 3)
You are monitoring an Azure Stream Analytics job by using metrics in Azure.
You discover that during the last 12 hours, the average watermark delay is consistently greater than the configured late arrival tolerance.
What is a possible cause of this behavior?

1. A. Events whose application timestamp is earlier than their arrival time by more than five minutes arrive as inputs.
2. B. There are errors in the input data.
3. C. The late arrival policy causes events to be dropped.
4. D. The job lacks the resources to process the volume of incoming data.

Correct Answer: D
Watermark Delay indicates the delay of the streaming data processing job.
There are a number of resource constraints that can cause the streaming pipeline to slow down. The watermark delay metric can rise due to:
Not enough processing resources in Stream Analytics to handle the volume of input events. To scale up
resources, see Understand and adjust Streaming Units.
Not enough throughput within the input event brokers, so they are throttled. For possible solutions, see Automatically scale up Azure Event Hubs throughput units.
Output sinks are not provisioned with enough capacity, so they are throttled. The possible solutions vary widely based on the flavor of output service being used.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-time-handling