DP-203 Practice Test 33 — 15 Questions

Question 1

You need to design a storage solution for streaming data from IoT devices. The solution must support real-time analytics and long-term storage for historical analysis. Which combination of Azure services should you use?

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

Accepted Answer

Azure Event Hubs and Azure Data Lake Storage Gen2. Azure Event Hubs is designed for high-throughput, low-latency ingestion of streaming data from IoT devices, supporting real-time analytics via integration with Azure Stream Analytics. Azure Data Lake Storage Gen2 provides hierarchical namespace and POSIX-compliant access for long-term storage, enabling efficient historical analysis with tools like Azure Synapse Analytics or Spark. This combination meets both real-time and historical requirements without the limitations of other options.

Answer

Azure Queue Storage and Azure Cosmos DB

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Azure Event Hubs and Azure Blob Storage

Answer

Azure IoT Hub and Azure SQL Database

Question 2

You are a data engineer at a healthcare analytics company. The company uses Azure Data Factory (ADF) to orchestrate data pipelines that ingest patient data from on-premises SQL Server databases into Azure Synapse Analytics. Recently, the pipeline has been failing intermittently with the following error: 'Failure happened on 'Sink' side. ErrorCode=SqlFailedToConnect, Type=Microsoft.DataTransfer.Common.Shared.HybridDeliveryException, Message=Cannot connect to SQL Server Database. The TCP connection to the host <server_name>, port 1433 has failed. Error: 'Connection timed out.'.' The on-premises SQL Server is behind a corporate firewall. The ADF self-hosted integration runtime (SHIR) is installed on a VM inside the corporate network. You have verified that the SHIR is running and that the SQL Server is accessible from the SHIR VM using SQL Server Management Studio (SSMS). The error occurs sporadically, not consistently. What is the most likely cause of the intermittent connection timeout?

Accepted Answer

The corporate firewall or network device is closing idle TCP connections to the SQL Server database.. The intermittent nature of the timeout, combined with the fact that the SHIR VM can connect to SQL Server via SSMS, strongly suggests that the corporate firewall or a network intermediary (such as a load balancer or NAT device) is closing idle TCP connections. ADF pipelines may hold connections open between activities or during long-running data transfers, and if no keep-alive packets are sent within the firewall's idle timeout window (commonly 4–30 minutes), the firewall drops the TCP session. When ADF attempts to reuse that connection, it receives a 'Connection timed out' error because the socket is no longer valid.

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The data being transferred is skewed, causing the sink to be overwhelmed.

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The SQL Server database is experiencing high CPU utilization during the pipeline execution window.

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The self-hosted integration runtime is running out of memory during peak loads.

Question 3

Your company has a data lake in Azure Data Lake Storage Gen2 that stores sensitive customer information. You need to implement fine-grained access control so that data engineers can read all data, data scientists can read only anonymized data, and auditors can view access logs. The solution must use Azure role-based access control (RBAC) and access control lists (ACLs). You also need to enable auditing of read operations. What should you do?

Accepted Answer

Assign Storage Blob Data Contributor RBAC role to data engineers at the storage account level, use ACLs to deny read access to raw data for data scientists, and enable diagnostic settings for read requests to Log Analytics.. To implement fine-grained access control in Azure Data Lake Storage Gen2, combine Azure RBAC roles for coarse permissions (e.g., Storage Blob Data Contributor for data engineers at the storage account level) and ACLs for fine-grained control (e.g., deny read on raw data for data scientists). Enable diagnostic settings for read requests to Log Analytics to audit read operations. Option A is incorrect because assigning Storage Blob Data Reader to data scientists would give them read access to all data, not just anonymized data, and lifecycle management does not control access. Option C is incorrect because Storage Analytics logs are deprecated; diagnostic settings should be used instead. Option D is incorrect because granting read access to all users at the container level is overly permissive and does not provide fine-grained control; Azure Policy is for compliance, not access control.

Answer

Use Azure RBAC to assign Storage Blob Data Reader to data scientists, and configure lifecycle management to move raw data to archive tier.

Answer

Assign RBAC roles at the storage account level and enable Storage Analytics logs for read operations.

Answer

Assign RBAC roles at the container level to grant read access to all users, and use Azure Policy to audit access.

Question 4

You have an Azure Databricks workspace that uses a managed resource group. The security team requires that all cluster nodes use no public IP addresses and that all outbound traffic goes through a firewall. What should you configure?

Accepted Answer

Deploy the workspace in a VNet with forced tunneling enabled and a firewall.. Deploying the Azure Databricks workspace in a VNet with forced tunneling enabled and a firewall ensures that cluster nodes have no public IP addresses and all outbound traffic is routed through the firewall. Option A is incorrect because service endpoints do not prevent public IPs on cluster nodes. Option C is incorrect because NSGs alone do not force traffic through a firewall; forced tunneling requires a route table with default route to the firewall. Option D is incorrect because Azure Private Link only provides private connectivity to the workspace, but does not control outbound traffic from cluster nodes.

Answer

Configure service endpoints for Azure Storage and Azure Data Lake Storage.

Answer

Apply network security groups (NSGs) to the subnet that restrict outbound traffic.

Answer

Enable Azure Private Link for the Databricks workspace.

Question 5

You are designing a data storage solution that must support both operational and analytical workloads using a single copy of data. Which TWO technologies should you consider?

Accepted Answer

Azure Synapse Link for Cosmos DB. The requirement is to support both operational and analytical workloads on a single copy of data, which is characteristic of HTAP (Hybrid Transactional/Analytical Processing) solutions. Among the options, Azure Synapse Link for Cosmos DB (D) and Azure Cosmos DB with analytical store (HTAP) (E) are specifically designed for HTAP, synchronizing operational data to an analytical store without separate copies. Azure SQL Database with materialized views (A) improves query performance but does not enable HTAP on a single copy; change data capture (B) tracks changes but is not HTAP; and PolyBase (C) is a data virtualization tool that queries external data sources, not an in-database HTAP solution. Therefore, D and E are correct.

Answer

Azure SQL Database with materialized views

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Azure SQL Database with change data capture (CDC)

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Azure SQL Database with PolyBase

Question 6

You are troubleshooting slow COPY INTO performance in Azure Synapse Analytics dedicated SQL pool when loading Parquet files from Azure Data Lake Storage Gen2. The files are 1 GB each. What should you do to improve performance?

Accepted Answer

Increase the number of files to match the number of distributions. COPY INTO in Azure Synapse dedicated SQL pool distributes data across 60 distributions. To maximize parallelism, the number of input files should match or exceed the number of distributions. With 1 GB files, you have too few files to fully utilize all distributions, causing some distributions to remain idle. Increasing the number of files to at least 60 ensures each distribution gets work, improving throughput.

Answer

Reduce the file size to 100 MB to increase parallelism

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Use PolyBase instead of COPY INTO

Answer

Disable parallel processing in the COPY command

Question 7

You are reviewing a script to create an external data source in Azure Synapse Analytics serverless SQL pool. Based on the exhibit, what is the purpose of the SAS token?

Accepted Answer

To provide read access to the container for querying data.. The SAS token grants read and list permissions (sp=rl) to the container, which allows the serverless SQL pool to read data from the container. Option B is incorrect because the SAS token does not have write permission (sp=rl, no write). Option C is incorrect because the SAS token does not encrypt the connection; it provides delegated access. Option D is incorrect because the SAS token is used in the credential to access storage, not to authenticate to the serverless SQL pool.

Answer

To provide write access to the container for storing query results.

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To encrypt the connection between the serverless pool and storage.

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To authenticate the user to the serverless SQL pool.

Question 8

You are designing a data lakehouse architecture in Azure using Delta Lake. The solution needs to process batch and streaming data from multiple sources, including IoT devices and CRM systems. You need to ensure data quality by enforcing schema validation and handling schema evolution. You also need to provide a unified catalog for querying. Which service should you use?

Accepted Answer

Azure Databricks Unity Catalog. Azure Databricks Unity Catalog provides a unified governance solution for data and AI, including schema enforcement and evolution for Delta Lake. Option A is wrong because Azure Purview is for data discovery and lineage, not for schema enforcement. Option B is wrong because Azure Data Lake Storage Gen2 is storage only, not a catalog or governance layer. Option C is wrong because Azure Synapse Analytics serverless SQL pool is a query engine and does not provide the same schema management features as Unity Catalog.

Answer

Azure Purview

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Azure Data Lake Storage Gen2

Answer

Azure Synapse Analytics serverless SQL pool

Question 9

You are monitoring the performance of an Azure Data Factory pipeline that uses a Copy activity to load data into Azure Synapse Analytics. Which THREE metrics should you monitor to identify potential performance bottlenecks?

Accepted Answer

Throughput (data read/written per second).. Options A, D, and E are correct. Throughput (data read/written per second), Copy activity duration, and Data read and written metrics are direct indicators of performance bottlenecks in the Copy activity. Option B is incorrect because Integration runtime CPU utilization is not a standard metric exposed by Azure Data Factory for monitoring Copy activity performance; it reflects runtime resource usage but not directly the data transfer performance. Option C is incorrect because Pipeline run duration includes overhead from orchestration, such as pipeline activity scheduling and coordination, and is not a precise measure of the Copy activity's data transfer performance.

Answer

Integration runtime CPU utilization.

Answer

Pipeline run duration.

Question 10

You are designing a data storage solution for a healthcare company that must comply with HIPAA. The solution needs to store structured patient records and unstructured medical images. Data must be encrypted at rest and in transit. Which TWO storage solutions meet these requirements?

Accepted Answer

Azure Blob Storage. Azure Blob Storage supports storing unstructured data like medical images and offers encryption at rest via Storage Service Encryption (SSE) and in transit via HTTPS/TLS. It is HIPAA-eligible when configured with appropriate access controls and logging, making it suitable for the unstructured image component of the solution.

Answer

Azure Redis Cache

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Azure Table Storage

Answer

Azure Cosmos DB

Question 11

You are a data engineer for a financial services company. The company uses Azure Data Lake Storage Gen2 as its data lake. You have a directory structure where each customer has a folder containing transaction files in CSV format. The security team requires that each customer's data be accessible only to that customer's users. You need to implement fine-grained access control using Azure Data Lake Storage Gen2's POSIX-like ACLs. However, you have thousands of customers, and managing ACLs individually is not feasible. What should you do?

Accepted Answer

Create an Azure AD group for each customer, add users to the group, and assign ACLs to the group on the customer folder. Azure Data Lake Storage Gen2 supports POSIX-like ACLs that can be assigned to Azure AD security groups. By creating one Azure AD group per customer, adding the customer's users to that group, and then assigning the group the appropriate read/execute ACLs on the customer's folder, you achieve scalable, fine-grained access control without managing thousands of individual user ACLs. This approach aligns with the principle of least privilege and simplifies administration.

Answer

Create a shared access signature (SAS) token for each customer and distribute it securely

Answer

Use POSIX ACLs on each customer folder, assigning permissions to individual user identities

Answer

Use row-level security in Azure Data Lake Storage Gen2

Question 12

You are a data engineer for a financial services company. You have an Azure Data Lake Storage Gen2 account containing historical trade data organized by date in the format 'yyyy/MM/dd'. Each day's data is stored as a collection of Parquet files. The data is used by a team of analysts who run ad-hoc queries using Azure Synapse Serverless SQL. Recently, the analysts have reported that queries scanning multiple months of data are slow. The storage account uses LRS with a general-purpose v2 tier. You have enabled hierarchical namespace. The data is not partitioned in any other way. You need to improve query performance without moving data or changing the storage tier. What should you do?

Accepted Answer

Create external tables with partition definition using the directory structure and ensure queries filter on the date column.. Azure Synapse Serverless SQL can leverage the directory structure of Azure Data Lake Storage Gen2 as virtual partitions. By creating external tables with a partition definition that maps to the 'yyyy/MM/dd' folder hierarchy and ensuring queries filter on the date column, the serverless SQL engine performs partition elimination. This reduces the amount of data scanned, directly addressing the slow performance when querying multiple months of data without moving data or changing the storage tier.

Answer

Increase the query timeout setting in Azure Synapse Studio.

Answer

Redistribute the data using hash distribution on the date column.

Answer

Increase the data warehouse units (DWU) for the serverless SQL endpoint.

Question 13

You are using Azure Data Factory to ingest data from a REST API into Azure Synapse Analytics. The API has a rate limit of 100 requests per minute. You need to ensure that the pipeline respects the rate limit and retries on failure. Which two settings should you configure in the copy activity? (Choose two.)

Accepted Answer

Set the 'Throttle' property to limit the number of concurrent connections.. Options C and D are correct. Setting the 'Throttle' property (or 'maxConcurrentConnections') limits the number of concurrent connections to the REST API, which helps respect the rate limit of 100 requests per minute. Setting the 'Retry' property to a value greater than 0 enables the activity to retry on transient failures. Option A is wrong because 'Enable staging' is used for large data transfers or to enable PolyBase, not for rate limiting. Option B is wrong because 'Batch size' controls the number of rows per batch for bulk operations, not the request rate. Option E is wrong because 'Timeout' specifies the maximum duration of the activity, not retry behavior.

Answer

Enable 'Enable staging' to use a staging blob.

Answer

Configure the 'Batch size' to 100.

Answer

Increase the 'Timeout' value to 10 minutes.

Question 14

You are implementing a data lake using Azure Data Lake Storage Gen2. Which THREE actions should you take to secure the data at rest and in transit?

Accepted Answer

Enable Azure Storage Service Encryption (SSE) for data at rest. Azure Storage Service Encryption (SSE) automatically encrypts data at rest using 256-bit AES encryption, which is transparent to applications and meets compliance requirements. This is a fundamental security control for protecting data stored in Azure Data Lake Storage Gen2.

Answer

Enable TLS 1.0 for compatibility with legacy clients

Answer

Configure firewall rules to allow only trusted IPs

Question 15

You are designing a data processing solution that requires exactly-once processing semantics for streaming data. Which two Azure services support exactly-once processing? (Choose two.)

Accepted Answer

Azure Stream Analytics. Azure Stream Analytics supports exactly-once processing by using checkpointing and event sourcing to ensure that each event is processed exactly once, even in the event of failures or restarts. It achieves this through its internal state management and the use of checkpoint offsets in the output sink, guaranteeing no duplicate or missed events.

Answer

Azure Event Hubs

Answer

Azure Data Lake Storage Gen2