DP-203 Practice Test 42 — 15 Questions

Question 1

You are building a data processing pipeline in Azure Synapse Analytics that ingests data from Azure Blob Storage and writes to a dedicated SQL pool. You need to ensure the pipeline can handle schema changes in the source data without failing. Which TWO actions should you take?

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

Accepted Answer

Enable schema drift in a Mapping Data Flow activity.. Mapping Data Flows in Azure Synapse Analytics support schema drift, which allows the pipeline to dynamically handle changes in source data structure (e.g., new columns, changed data types) without failing. By enabling schema drift, the data flow can automatically detect and propagate these changes downstream, ensuring resilience against schema evolution.

Answer

Use staged copy with an intermediate storage.

Answer

Define a fixed schema in the source dataset.

Answer

Use PolyBase to load data into the dedicated SQL pool.

Question 2

You are designing a data processing solution in Azure Databricks. The data is stored in Azure Data Lake Storage Gen2 and you need to perform transformations using Apache Spark. The security requirements mandate that all data in transit must be encrypted and that the storage account must not be accessible from the public internet. What should you configure?

Accepted Answer

Enable the storage account firewall and add a private endpoint for Azure Databricks to use.. It satisfies both security requirements: encrypting data in transit and preventing public internet access. A private endpoint uses Azure Private Link to connect Azure Databricks to the storage account over the Microsoft backbone network, ensuring all traffic stays within the Azure network and is encrypted via TLS. The storage account firewall is then configured to deny all public traffic, so only the private endpoint can access the storage account, meeting the 'not accessible from the public internet' mandate.

Answer

Disable TLS on the storage account and use a shared access signature (SAS) token for authentication.

Answer

Use Azure Databricks with VNet injection and configure a service endpoint for the storage account.

Answer

Configure the storage account to use HTTPS only and enable firewall rules to allow only Azure services.

Question 3

Which THREE components are required to implement a real-time data processing solution using Azure Stream Analytics?

Accepted Answer

An input source such as Azure Event Hubs or IoT Hub. Azure Stream Analytics requires a streaming input source to ingest real-time data. Azure Event Hubs and IoT Hub are the primary services that provide high-throughput, low-latency event ingestion, which Stream Analytics can consume via its built-in connector. Without a streaming input, the job cannot process real-time data.

Answer

Power BI as the output sink

Answer

Azure Data Factory pipeline for orchestration

Question 4

You have an Azure Data Lake Storage Gen2 account that stores sensitive customer data. You need to prevent data exfiltration to unauthorized external IP addresses. Which TWO actions should you take?

Accepted Answer

Use private endpoints for the storage account. Network security controls: enabling the storage firewall to allow only specific virtual networks (Option D) restricts access to traffic originating from those VNets, blocking external IPs. Using private endpoints (Option A) ensures that all traffic to the storage account stays within the Microsoft backbone network, preventing exposure to the public internet. Option B is incorrect because Azure Firewall is a separate service, not a storage account setting. Option C (SAS) provides fine-grained access control but does not prevent exfiltration from external IPs. Option E (GRS) is for data durability, not security.

Answer

Enable Azure Firewall on the storage account

Answer

Use shared access signatures (SAS) with limited permissions

Answer

Enable geo-redundant storage (GRS)

Question 5

Match each Azure monitoring service to its function.

Accepted Answer

Azure Monitor: Collects and analyzes telemetry from cloud and on-premises environments.. The correct matches are: Azure Monitor collects telemetry, Azure Log Analytics queries logs, Azure Application Insights monitors web apps, and Azure Service Health provides service health alerts. Common confusions occur between Azure Monitor and Application Insights, and between Azure Monitor and Log Analytics.

Answer

Azure Monitor: Monitors live web applications, detects anomalies, and analyzes performance.

Answer

Azure Log Analytics: Collects and analyzes telemetry from cloud and on-premises environments.

Question 6

Match each data transformation concept to its definition.

Accepted Answer

PolyBase: A technology that allows querying external data sources like Hadoop or Azure Blob Storage using T-SQL.. The correct matches are: PolyBase queries external data via T-SQL; Data Lake is a raw data repository; ELT loads before transforming; Azure Data Factory is a cloud integration service. Common confusions include mixing up PolyBase with Data Lake, or ELT with Azure Data Factory.

Answer

PolyBase: A storage repository that holds a vast amount of raw data in its native format.

Answer

ELT: A cloud-based data integration service that orchestrates and automates data movement and transformation.

Question 7

You are optimizing an Azure Synapse Analytics dedicated SQL pool that is experiencing high concurrency and frequent resource class contention. You need to improve query performance and reduce contention without changing the workload. Which two actions should you take? (Choose two.)

Accepted Answer

Implement workload isolation to separate critical queries into dedicated resource groups.. Options B and D are correct. Workload isolation and workload classification help manage resource allocation and reduce contention. Option A is wrong because increasing DWU may help but does not address contention directly. Option C is wrong because materialized views improve performance but do not reduce contention. Option E is wrong because result set caching helps read workloads but not contention.

Answer

Increase the DWU (Data Warehouse Units) to allocate more resources.

Answer

Create materialized views to pre-aggregate data.

Answer

Enable result set caching to reduce repeated query execution.

Question 8

You are designing a batch processing solution in Azure Databricks that reads Parquet files from Azure Data Lake Storage Gen2, performs aggregations, and writes results to a Delta table. The data volume is expected to grow to 10 TB per batch. You need to minimize shuffle operations during the aggregation step. Which approach should you recommend?

Accepted Answer

Partition the Delta table by the aggregation key and use the same partitioning when reading.. Partitioning the Delta table by the aggregation key and aligning the read partitioning ensures that data with the same key value is co-located in the same Spark partition. This allows the aggregation to be performed within each partition without needing to shuffle data across the network, which is the primary cause of performance bottlenecks in large-scale batch processing.

Answer

Use bucketing on a different column to reduce partition skew.

Answer

Use a broadcast join to avoid shuffle on the aggregation.

Answer

Use coalesce to reduce the number of partitions before aggregation.

Question 9

Your team uses Azure Data Factory to orchestrate data movement. You need to monitor pipeline runs and set up alerts when a pipeline fails more than three times in an hour. What is the most efficient approach?

Accepted Answer

Create an Azure Monitor metric alert for the 'Failed pipeline runs' metric with a threshold of 3 in 1 hour.. Azure Monitor alerts can be configured based on metrics like Failed pipeline runs with a threshold of 3 in 1 hour. Option A is wrong because Alert rules in Data Factory are limited. Option B is wrong because diagnostic settings send logs to Log Analytics, but you would need to create a log alert, which is less efficient than a metric alert. Option C is wrong because a logic app is not the most efficient for simple threshold alerts.

Answer

Create an alert rule in Azure Data Factory based on the 'Failed pipeline runs' metric.

Answer

Configure diagnostic settings to send logs to Log Analytics and create a log alert.

Answer

Use a Logic App to periodically check the pipeline run status and send notifications.

Question 10

You are designing a data processing solution in Azure Databricks that uses Unity Catalog. The security team requires that all users authenticate using Microsoft Entra ID and that access to tables is governed by attribute-based access control (ABAC) using table tags. Which feature should you enable?

Accepted Answer

Table tags with access control lists (ACLs) in Unity Catalog. [CORRECT]. In Unity Catalog, attribute-based access control (ABAC) is implemented through table tags combined with access control lists (ACLs). Table tags allow data to be classified, and ACLs can then be configured based on those tags to enforce attribute-based access. This directly satisfies the requirement of using table tags for ABAC. Option B (dynamic views with user context functions) can provide similar controls but does not inherently leverage table tags and is not the dedicated ABAC feature in Unity Catalog.

Answer

Column-level security masks. [wrong]

Answer

Dynamic views with user context functions. [wrong]

Answer

Row-level security filters. [wrong]

Question 11

You need to ensure that an Azure Synapse Analytics serverless SQL pool automatically pauses after 2 hours of inactivity to save costs. Which feature should you configure?

Accepted Answer

Auto-pause feature. The Auto-pause feature in Azure Synapse Analytics serverless SQL pools automatically suspends the pool after a period of inactivity (default 1 hour, configurable up to 8 hours), reducing costs when not in use. Option C is correct because it directly addresses the requirement to pause after 2 hours of inactivity.

Answer

Maintenance window

Answer

Data Exfiltration Prevention

Answer

Workload Management

Question 12

You need to ensure that data stored in Azure Data Lake Storage Gen2 is encrypted at rest using customer-managed keys. Which Azure service should you use to manage the keys?

Accepted Answer

Azure Key Vault. Azure Key Vault is used to store customer-managed keys for Azure Storage encryption. Option B is wrong because Microsoft Purview is for data governance. Option C is wrong because Azure Confidential Computing is for compute. Option D is wrong because Microsoft Entra ID is for identity.

Answer

Microsoft Purview

Answer

Azure Confidential Computing

Answer

Microsoft Entra ID

Question 13

A company uses Azure Synapse Analytics dedicated SQL pool for a data warehouse. They notice that some queries are using more memory than expected, causing resource contention. Which TWO actions should they take to diagnose and optimize memory usage?

Accepted Answer

Increase the resource class for the users running the heavy queries.. Increasing the resource class for users running heavy queries allocates more memory to those queries, reducing resource contention by ensuring they have sufficient memory to execute efficiently. Option D is correct because querying sys.dm_pdw_exec_requests DMV allows you to identify queries with high memory grants, which is the first step in diagnosing which queries are consuming excessive memory and need optimization.

Answer

Enable result-set caching.

Answer

Scale up the DWU setting.

Answer

Rebuild clustered columnstore indexes.

Question 14

Which TWO actions can you take to optimize the performance of a dedicated SQL pool in Azure Synapse Analytics when loading large volumes of data?

Accepted Answer

Use ROUND_ROBIN distribution for the staging table. Using ROUND_ROBIN distribution for a staging table ensures that data is evenly distributed across all distributions without any data movement, which is the fastest way to load data into a dedicated SQL pool. This distribution type is ideal for staging tables because it minimizes load time and avoids the overhead of hash distribution key computation during the initial data ingestion phase.

Answer

Create nonclustered indexes on all columns of the target table

Answer

Set the row group size to 100,000 rows for optimal compression

Answer

Enable change tracking on the target table

Question 15

You need to monitor the performance of Azure Synapse Analytics dedicated SQL pool queries. Which Azure service should you use to identify long-running queries and resource bottlenecks?

Accepted Answer

Azure Synapse Studio monitoring hub and dynamic management views (DMVs).. Azure Synapse Studio monitoring hub provides a centralized view of dedicated SQL pool activity, including running and completed queries, and dynamic management views (DMVs) can be queried to identify long-running queries and resource bottlenecks. Option A is wrong because Microsoft Purview Data Map is a data governance and cataloging service, not a performance monitoring tool. Option C is wrong because Azure Log Analytics queries can be used for historical analysis but require configuration and are not the primary tool for real-time live query monitoring in Synapse dedicated SQL pools. Option D is wrong because Azure Monitor Workbooks provide customizable dashboards for various Azure services, but they are not specifically designed for direct query monitoring in Synapse SQL pools.

Answer

Microsoft Purview Data Map.

Answer

Azure Log Analytics queries.

Answer

Azure Monitor Workbooks.