DP-203 Practice Test 4 — 10 Questions

Question 1

You are designing a stream processing solution using Azure Stream Analytics. The job must reference a static lookup table (product catalog) stored in Azure Blob Storage. The catalog is updated once daily. The job should automatically pick up the latest version without restarting. Which two configurations are required? (Choose two.)

Accepted Answer

Set the reference input's 'Path pattern' to include date and time placeholders. Option B is correct because Azure Stream Analytics reference data inputs support path pattern placeholders like {date} and {time} to dynamically resolve the latest blob file. This allows the job to automatically load a new version of the static lookup table when the blob is updated, without requiring a job restart. The path pattern must be structured to match the naming convention of the uploaded file, such as 'catalog/{date}/{time}/products.csv'.

Answer

Configure the reference input with a static blob path

Answer

Use Azure Event Grid to trigger job restart on blob update

Answer

Store the reference data in Azure SQL Database instead of Blob Storage

Question 2

When designing a data processing solution using Azure Databricks, what is the recommended approach to handle schema evolution when reading data from Delta Lake tables?

Accepted Answer

Set the option 'mergeSchema' to 'true' on write. Option A is correct because in Delta Lake, schema evolution is automatically handled by setting the 'mergeSchema' option to 'true' on write operations. This allows new columns to be added or existing column types to be safely widened without manual intervention, preserving existing data and metadata integrity.

Answer

Set the option 'overwriteSchema' to 'true' on write

Answer

Manually alter the table schema using ALTER TABLE

Answer

Ignore schema changes and use 'failOnDataLoss' flag

Question 3

You are implementing a data pipeline using Azure Data Factory. The source is an on-premises SQL Server database. Which Azure Data Factory component is required to connect to the on-premises data source?

Accepted Answer

Self-hosted Integration Runtime. A self-hosted integration runtime (IR) is required to connect Azure Data Factory to on-premises SQL Server because it provides the compute environment for data movement between on-premises networks and Azure. It must be installed on a machine inside the corporate firewall, enabling secure communication via outbound HTTPS (port 443) to Azure. This is the only IR type that can access private, on-premises data sources directly.

Answer

Azure Integration Runtime

Answer

Managed Virtual Network Integration Runtime

Answer

Azure Data Factory Gateway

Question 4

A company uses Azure Synapse Analytics dedicated SQL pool. They notice that queries against a large fact table are running slower over time. The table is hash-distributed on a date key and has a clustered columnstore index. Which action should you take to improve query performance?

Accepted Answer

Rebuild the clustered columnstore index.. Over time, columnstore indexes can become fragmented due to insert, update, and delete operations, leading to compressed row groups that are not optimally sized or have deleted records. Rebuilding the clustered columnstore index reorganizes the data into fully compressed row groups, removes deleted rows, and restores the high compression and segment elimination that columnstore indexes rely on for fast query performance.

Answer

Add a non-clustered index on frequently filtered columns.

Answer

Change the distribution column to a column with higher cardinality.

Answer

Change the distribution to round-robin.

Question 5

You are tuning an Azure Stream Analytics job that reads from an Event Hub and writes to an Azure Synapse Analytics table. The job's SU% utilization is consistently at 90%. Which action would most likely reduce the SU% utilization?

Accepted Answer

Increase the number of streaming units (SU) allocated to the job.. Increasing the number of streaming units (SU) allocated to the job directly adds more compute resources, which reduces the SU% utilization by distributing the workload across more SUs. Since the job is consistently at 90% utilization, adding SUs lowers the per-SU load, preventing throttling and improving throughput. This is the standard scaling approach for Azure Stream Analytics when SU% is high.

Answer

Decrease the Event Hub throughput units.

Answer

Partition the output table in Azure Synapse Analytics.

Answer

Use a reference data join to filter events.

Question 6

You are monitoring an Azure Cosmos DB account using Azure Monitor. The 'Normalized RU Consumption' metric for a container is consistently above 90%. You need to ensure that the container can handle the load without throttling. What should you do?

Accepted Answer

Increase the provisioned throughput (RU/s) for the container.. The 'Normalized RU Consumption' metric indicates the percentage of provisioned throughput (RU/s) being used. Consistently above 90% means the container is operating near its capacity limit, risking throttling (HTTP 429 errors) during traffic spikes. Increasing the provisioned throughput (RU/s) directly raises the capacity, allowing the container to handle the load without throttling.

Answer

Change the partition key to a different property.

Answer

Switch the account to serverless mode.

Answer

Modify the indexing policy to exclude unused paths.

Question 7

Which THREE factors should you consider when designing a monitoring strategy for Azure Synapse Analytics dedicated SQL pool performance?

Accepted Answer

Use dynamic management views (DMVs) to identify long-running queries.. Option A is correct because dynamic management views (DMVs) in Azure Synapse Analytics dedicated SQL pool, such as sys.dm_pdw_exec_requests and sys.dm_pdw_request_steps, provide real-time insight into query execution, allowing you to identify long-running queries, monitor resource consumption, and detect performance bottlenecks. This is a foundational monitoring practice for tuning workload performance.

Answer

Ensure data is evenly distributed across distributions.

Answer

Configure automatic index rebuild for columnstore indexes.

Question 8

You are reviewing an Azure Policy assignment that uses the above JSON to define a role-based access control (RBAC) action. What is the primary purpose of this policy?

Accepted Answer

To authorize generation of a shared access signature (SAS) token for the storage account.. The policy JSON defines a role-based access control (RBAC) action that grants the 'Microsoft.Storage/storageAccounts/listAccountSas/action' permission. This specific action authorizes the generation of a shared access signature (SAS) token at the storage account level, not at the container or blob level. Therefore, the primary purpose is to allow the generation of an account SAS token, which provides delegated access to storage services.

Answer

To assign RBAC roles to users for the storage account.

Answer

To enable delegation of access to a specific blob.

Answer

To allow users to set permissions on storage account containers.

Question 9

A data engineer monitors an Azure Stream Analytics job that processes real-time data. The job is falling behind, and the SU utilization is at 100%. Which action should be taken to improve performance?

Accepted Answer

Increase the number of Streaming Units (SU).. When SU utilization reaches 100%, the job is fully saturated and cannot process incoming data fast enough. Increasing the number of Streaming Units (SU) allocates more compute resources (CPU and memory) to the job, allowing it to handle higher throughput and reduce backlog. This is the direct and recommended action for resolving performance bottlenecks caused by insufficient SU capacity.

Answer

Reduce the number of Streaming Units.

Answer

Change the query compatibility level to 1.0.

Answer

Deploy a second Stream Analytics job and split the input.

Question 10

Which TWO actions should you take to reduce costs associated with an Azure Synapse Dedicated SQL Pool that is used for reporting during business hours only?

Accepted Answer

Pause the pool during non-business hours.. Option A is correct because pausing a Dedicated SQL Pool stops billing for compute resources (DWU) while retaining storage costs. Since the pool is only needed for reporting during business hours, pausing it during non-business hours directly eliminates compute charges for that period, which is the most significant cost driver.

Answer

Enable advanced data compression on all tables.

Answer

Scale down the pool during business hours.

Answer

Change the distribution of large tables to ROUND_ROBIN.