DP-203 Practice Test 24 — 15 Questions

Question 1

Refer to the exhibit. You have an Azure Data Factory with two triggers defined as shown. The DailyTrigger runs the CopyPipeline every day at midnight UTC. The BlobTrigger runs the ProcessPipeline when a blob is created in the /input/ folder. You notice that the ProcessPipeline is not executing even though blobs are being created. What is the most likely cause?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

The storage account does not have an event subscription configured for blob creation.. The most likely cause is that the storage account does not have an event subscription configured for blob creation. The BlobEventsTrigger in Azure Data Factory relies on an event subscription from the storage account to the trigger. Without this subscription, the trigger will not fire even when blobs are created in the specified path. Option D correctly identifies this issue. Option A is incorrect because the blobPathBeginsWith property includes the container name prefix; Option B is incorrect because the trigger is configured to listen to blob creation events; Option C is incorrect because the ProcessPipeline does not require parameters from the trigger.

Answer

The blobPathBeginsWith property is missing the container name.

Answer

The BlobEventsTrigger is configured to listen to the wrong event type.

Answer

The ProcessPipeline expects parameters that are not provided by the trigger.

Question 2

Your organization uses Azure Data Lake Storage Gen2 and needs to prevent accidental deletion of data by enabling soft delete. You also need to ensure that deleted blobs are recoverable for 30 days. What should you configure?

Accepted Answer

Enable blob soft delete and set retention period to 30 days.. Blob soft delete enables recovery of deleted blobs within a specified retention period (30 days in this case). Option A is incorrect because blob snapshots are point-in-time copies that require manual management and do not provide automatic recovery of deleted blobs. Option B is incorrect because Azure Backup is designed for virtual machines and other Azure resources, not for blob-level recovery in Data Lake Storage Gen2. Option C is incorrect because container soft delete deletes entire containers, not individual blobs.

Answer

Enable blob snapshots and set them to expire after 30 days.

Answer

Use Azure Backup to create daily backups of the storage account.

Answer

Enable container soft delete with a retention period of 30 days.

Question 3

You are designing a disaster recovery plan for an Azure Synapse Analytics dedicated SQL pool. The primary region becomes unavailable. You need to fail over to a secondary region with minimal data loss. The recovery point objective (RPO) is 1 hour. What should you configure?

Accepted Answer

Enable geo-backup on the dedicated SQL pool.. Geo-backup is a built-in feature for Azure Synapse Analytics dedicated SQL pools that automatically takes full backups at regular intervals and replicates them to a paired region. The default recovery point objective (RPO) is 1 hour, meeting the requirement. Option A is incorrect because active geo-replication is a feature for Azure SQL Database, not for Synapse dedicated SQL pools. Option B is incorrect because automatic restore points are local and not automatically replicated; copying them via Azure Data Factory adds complexity and does not guarantee the RPO. Option D is incorrect because user-defined restore points are manual and would require additional orchestration to store them in a secondary region, making it less reliable and harder to meet the 1-hour RPO consistently.

Answer

Configure active geo-replication to the secondary region.

Answer

Use automatic restore points and copy them to the secondary region using Azure Data Factory.

Answer

Create user-defined restore points every hour and store them in the secondary region.

Question 4

You need to audit all queries run against an Azure Synapse Analytics serverless SQL pool. What should you enable?

Accepted Answer

Azure SQL Auditing on the serverless SQL pool endpoint. Azure SQL Auditing is the correct feature to audit all queries against an Azure Synapse Analytics serverless SQL pool. It captures query logs at the server level, providing detailed information about database activities, including the actual query text. Option B (Azure Monitor diagnostic settings) is for collecting metrics and logs but not specific query text for auditing. Option C (Azure Policy) is used for enforcing compliance rules, not auditing queries. Option D (Microsoft Purview) is for data cataloging and governance, not query auditing.

Answer

Microsoft Purview to scan and catalog queries

Answer

Azure Policy to enforce auditing

Answer

Azure Monitor diagnostic settings

Question 5

You are reviewing an Azure Data Factory pipeline JSON that copies data from Azure Blob Storage to Azure SQL Database using a stored procedure. The pipeline fails with a 'Parameter supplied for object is not valid' error. What is the most likely cause?

Accepted Answer

The stored procedure parameters are not mapped to source columns.. The error 'Parameter supplied for object is not valid' in a copy activity using a stored procedure typically indicates that the stored procedure is expecting parameters that are not being provided correctly. The most common cause is that the source columns in the copy activity are not mapped to the stored procedure parameters. Option C is correct because the pipeline JSON likely lacks the necessary parameter mapping from source columns to stored procedure input parameters. Option A is incorrect because BlobSource is valid for Azure Blob Storage. Option B is incorrect because the error is about parameter supply, not the existence of a table type. Option D is incorrect because the error relates to parameter mapping, not dataset references.

Answer

The source type 'BlobSource' is not compatible with Azure Blob Storage.

Answer

The SQL table type 'dbo.InsertType' does not exist.

Answer

The dataset references are incorrect.

Question 6

Your company uses Azure Data Lake Storage Gen2. You need to ensure that data at rest is encrypted using a customer-managed key stored in Azure Key Vault. What should you configure?

Accepted Answer

Enable 'Azure Storage encryption' with customer-managed keys in the storage account's encryption blade.. Azure Storage encryption with customer-managed keys is configured in the encryption blade of the storage account. This ensures data at rest is encrypted using a key stored in Azure Key Vault. Option A is incorrect because Azure Policy can audit or enforce encryption but does not configure customer-managed keys. Option C is incorrect because client-side encryption encrypts data before it reaches Azure Storage, not at rest. Option D is incorrect because infrastructure encryption provides a second encryption layer but does not use customer-managed keys for the primary encryption.

Answer

Use Azure Policy to audit storage accounts without encryption.

Answer

Implement client-side encryption in the application code.

Answer

Enable 'Infrastructure encryption' for double encryption.

Question 7

You are configuring Azure Synapse Analytics dedicated SQL pool. To optimize query performance for a large fact table that is frequently filtered on date and region columns, which table distribution and indexing strategy should you recommend?

Accepted Answer

Hash distribution on region column with clustered columnstore index.. The best recommendation because hash distribution on the region column evenly distributes the data across distributions (assuming high cardinality), and clustering with a columnstore index provides excellent compression and query performance for large fact tables, especially when filtered on non-distribution columns like date. Option A (hash on date) risks data skew if date cardinality is low. Option B (replicated) is designed for small dimension tables, not large fact tables. Option C (round-robin) distributes rows randomly, preventing partition elimination and reducing filter performance.

Answer

Hash distribution on date column with clustered index.

Answer

Replicated distribution with heap index.

Answer

Round-robin distribution with clustered index.

Question 8

Your organization uses Azure Data Factory to orchestrate data pipelines. You need to ensure that sensitive data is not exposed in pipeline logs. What should you configure?

Accepted Answer

Enable 'Secure output' on pipeline activities.. Enabling 'Secure output' on pipeline activities prevents sensitive data from being written to Azure Data Factory logs. Option A is incorrect because while storing connection strings in Azure Key Vault is a security best practice, it does not prevent sensitive data from appearing in pipeline logs. Option C is incorrect because setting a retention policy for logs controls how long logs are kept, but does not prevent sensitive data exposure. Option D is incorrect because data flow debug logs are for debugging and do not mask sensitive data in pipeline logs.

Answer

Store connection strings in Azure Key Vault.

Answer

Set a retention policy for pipeline logs.

Answer

Use data flow debug logs with session logs.

Question 9

Refer to the exhibit. You have created the custom RBAC role shown and assigned it to a security group. Members of the group report that they can read blobs in the storage account but cannot list the contents of the container. What is the most likely reason for this issue?

Accepted Answer

The role does not include the permission to list blobs in a container.. The custom RBAC role includes the 'read' data action for blobs, which allows reading blob data, but it does not include the 'list' action for blobs. Without the 'list' permission, users cannot list the blobs within a container. In Azure RBAC for storage, the 'Microsoft.Storage/storageAccounts/blobServices/containers/blobs/read' action permits reading blob content and properties, but listing blobs requires the 'Microsoft.Storage/storageAccounts/blobServices/containers/blobs/list' action (or equivalent at the container level). Therefore, the role lacks the necessary permission to list blobs.

Option A is incorrect because custom RBAC roles are fully supported for Azure Data Lake Storage Gen2. Option B is incorrect because the scope of the role at the storage account level does not prevent listing blobs; the issue is missing data actions. Option D is incorrect because the role already includes the 'read' data action for blobs; the missing action is 'list'.

Answer

Custom roles are not supported for Azure Data Lake Storage Gen2.

Answer

The role is scoped to the storage account but not to the container.

Answer

The role lacks the 'read' data action for blobs.

Question 10

Which THREE metrics should you monitor to evaluate the performance of an Azure Stream Analytics job?

Accepted Answer

Input Events Backlogged. Watermark Delay (indicates latency), Input Events Backlogged (backlog of unprocessed events), and Output Events (throughput) are key performance metrics for an Azure Stream Analytics job. Option C (Conversion Errors) and Option D (SU (Memory) Utilization) are not performance metrics; Conversion Errors is an error metric, and SU Utilization is a resource metric.

Answer

Conversion Errors

Answer

SU (Memory) Utilization

Question 11

Your organization uses Azure Synapse Analytics with serverless SQL pools. You need to ensure that only users with specific Microsoft Entra ID roles can query external tables referencing Azure Data Lake Storage Gen2. What should you configure?

Accepted Answer

Grant SELECT permission on the external table to specific Microsoft Entra ID users or groups.. Granting SELECT permission on the external table directly controls which Microsoft Entra ID users or groups can query the data via the serverless SQL pool. This approach uses Azure AD authentication to restrict access at the query level, not at the storage layer. Option A is incorrect because assigning a managed identity to the serverless pool provides a service identity, but it does not restrict access per user. Option B is incorrect because Azure RBAC on the storage account grants data access at the storage level, not through the Synapse SQL engine, and does not limit querying via external tables. Option C is incorrect because the storage account firewall controls network access, not user identity, and does not prevent authorized users from other networks from querying.

Answer

Assign a managed identity to the serverless SQL pool and grant it Storage Blob Data Reader on the storage account.

Answer

Use Azure RBAC to assign Storage Blob Data Reader role to the users on the storage account.

Answer

Configure a storage account firewall to allow only the Synapse workspace IP range.

Question 12

Which THREE metrics from Azure Monitor should you use to evaluate the performance of an Azure Data Lake Storage Gen2 account?

Accepted Answer

Ingress. To evaluate the performance of an Azure Data Lake Storage Gen2 account, key metrics include Ingress (data written to the account), Success E2E Latency (end-to-end latency of successful requests), and Blob Count (total number of blobs/objects). Option A (Ingress) is correct because it measures the throughput of data entering the storage account. Option C (Success E2E Latency) is correct as it reflects the overall response time for successful operations. Option E (Blob Count) is correct because it helps assess scalability and cost. Options B (CPU Usage) and D (Available Storage Capacity) are not metrics for storage accounts; CPU is for compute resources, and capacity is a property, not a performance metric.

Answer

CPU Usage

Answer

Available Storage Capacity

Question 13

Which THREE methods can you use to monitor and optimize the performance of an Azure Data Lake Storage Gen2 account?

Accepted Answer

Enable Azure Monitor metrics for the storage account.. Options B, C, and E are correct. Azure Monitor metrics (B) provide performance data such as latency and throughput for the storage account. Lifecycle management policies (C) optimize costs by automatically moving data to cooler tiers based on access patterns, which can improve performance for frequently accessed data. Storage Analytics logs (E) capture detailed information about read and write requests, helping to identify performance bottlenecks. Option A (Azure Advisor) offers recommendations but is not a direct monitoring method; it is an advisory tool. Option D (Azure SQL Analytics) is designed for monitoring Azure SQL Database, not Azure Data Lake Storage Gen2.

Answer

Use Azure Advisor to get performance recommendations.

Answer

Use Azure SQL Analytics to query storage logs.

Question 14

Which THREE features should you use to optimize query performance in Azure Synapse Analytics dedicated SQL pool? (Choose three.)

Accepted Answer

Materialized views.. Options C, D, and E are correct. Materialized views precompute and store aggregated data, reducing compute for complex queries. Workload management with workload groups and importance allocates resources and prioritizes critical queries. Result-set caching stores the results of repeated queries, eliminating recomputation. Option A (T-SQL views) is a logical abstraction and does not inherently optimize performance. Option B (geo-redundant storage) provides disaster recovery but does not affect query performance.

Answer

T-SQL views.

Answer

Geo-redundant storage (GRS).

Question 15

You are monitoring an Azure Synapse Analytics dedicated SQL pool and notice that some queries are experiencing high wait times due to concurrency slots being exhausted. You need to optimize the workload to reduce contention. Which three actions should you take? (Select three.)

Accepted Answer

Create workload groups with different importance levels.. Options B, C, and D are correct. Workload groups with different importance levels allow you to prioritize critical queries, reducing contention. Workload isolation limits resources for a group, preventing resource-intensive queries from blocking others. Workload classification routes queries to appropriate groups based on criteria. Option A is incorrect because increasing DWU increases concurrency slots but may raise costs. Option E is incorrect because result-set caching does not affect concurrency slot usage.

Answer

Increase the data warehouse service level (DWU).

Answer

Enable result-set caching for frequently executed queries.