Microsoft · Free Practice Questions · Last reviewed May 2026
18real exam-style questions organised by domain, each with the correct answer highlighted and a plain-English explanation of why it's right — and why the others are wrong.
35% of exam · 6 sample questions below
Your organization uses Azure Synapse Analytics dedicated SQL pool. You need to ensure that all data at rest in the SQL pool is encrypted using a customer-managed key stored in Azure Key Vault. What should you configure?
Implement Always Encrypted with column encryption keys stored in Azure Key Vault.
Configure Dynamic Data Masking to obfuscate sensitive data.
Enable Azure Storage Service Encryption with a customer-managed key.
Enable Transparent Data Encryption (TDE) with a customer-managed key in Azure Key Vault.
TDE with customer-managed key provides encryption at rest for the entire database, meeting the requirement.
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?
Column-level security masks. [wrong]
Dynamic views with user context functions. [wrong]
Row-level security filters. [wrong]
Table tags with access control lists (ACLs) in Unity Catalog. [CORRECT]
Table tags with ACLs in Unity Catalog provide role-based access control (RBAC), not attribute-based access control (ABAC). ABAC requires dynamic views with user context functions.
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?
Configure service endpoints for Azure Storage and Azure Data Lake Storage.
Deploy the workspace in a VNet with forced tunneling enabled and a firewall.
VNet injection with forced tunneling ensures cluster nodes have no public IPs and all outbound traffic goes through the firewall.
Apply network security groups (NSGs) to the subnet that restrict outbound traffic.
Enable Azure Private Link for the Databricks workspace.
Refer to the exhibit. You are creating an Azure Storage account using an ARM template with the above snippet. After deployment, a security auditor reviews the configuration and notes that the storage account is not using a customer-managed key for encryption. What is the most likely reason?
The 'keyVersion' is missing a specific version, so Azure Storage defaults to Microsoft-managed key.
For customer-managed key, a specific key version is required; an empty version may cause Azure to use the latest but if the key is not accessible, it falls back to Microsoft-managed key.
The 'keySource' should be 'Microsoft.Storage' for customer-managed key.
The storage account requires double encryption to use customer-managed key.
The 'infrastructureEncryption' setting is enabled, which overrides customer-managed key.
You are monitoring an Azure Synapse Analytics dedicated SQL pool and notice that some queries are taking longer than expected. You need to identify queries that are experiencing significant memory pressure. Which dynamic management view (DMV) should you query?
sys.dm_pdw_exec_requests
This DMV includes memory_grant and memory_used columns to assess memory pressure.
sys.dm_pdw_wait_stats
sys.dm_pdw_query_stats_xe
sys.dm_pdw_nodes_os_performance_counters
You have an Azure Stream Analytics job that writes output to Azure Synapse Analytics. You need to ensure that the job can authenticate to Synapse Analytics using a managed identity. What should you do?
Enable system-assigned managed identity on the Stream Analytics job and configure the output to use it.
This is the correct method to use managed identity for authentication.
Generate a shared access signature (SAS) token for the Synapse Analytics workspace.
Create a user-assigned managed identity and assign it to the Stream Analytics job.
Configure the output to use SQL Server authentication with a username and password.
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Practice this domain19% of exam · 6 sample questions below
A company is designing a data lake solution on Azure Data Lake Storage Gen2. Data will be ingested from IoT devices at high frequency (every 5 seconds). Each device sends a JSON payload of 2 KB. The data must be stored in a hierarchical namespace and partitioned by date and device ID to optimize query performance. Which partition strategy should be used?
Use Azure SQL Database with clustered columnstore index on date and device ID.
Organize folders as /YYYY/MM/DD/DeviceID/ in ADLS Gen2 and use file naming that includes timestamp.
This folder structure enables efficient partition pruning based on date and device ID.
Use Azure Table Storage with PartitionKey set to date and RowKey set to device ID.
Use Azure Cosmos DB with partition key on (date, device ID) and TTL for data retention.
You are designing a near-real-time analytics pipeline for a retail company. Transaction data is generated in Azure SQL Database and must be replicated to Azure Synapse Analytics (dedicated SQL pool) with less than 5 minutes latency. The source table has 50 million rows and 200 columns, but only 30 columns are needed for analytics. Which approach should you recommend?
Use Azure SQL Database Change Tracking and push changes to Azure Event Hubs, then use Azure Stream Analytics to write to Synapse.
Enable Change Data Capture (CDC) on the source table and use Azure Data Factory with a 1-minute tumbling window to copy changes into Synapse.
CDC captures only changed rows, and ADF can run frequently to meet latency target.
Use Azure Synapse PolyBase to directly query the source SQL database every 5 minutes.
Schedule a full copy of the entire table every 5 minutes using Azure Data Factory.
A data engineer needs to store semi-structured JSON log files from a web application. Each log entry is about 1 KB. The logs are rarely queried (once a month) and must be retained for 7 years for compliance. The solution must minimize storage cost. Which storage option should be used?
Store the logs in Azure SQL Database as a table.
Store the logs in Azure Files share.
Store the logs in Azure Blob Storage with cool access tier.
Blob Storage cool tier is low-cost for infrequent access, suitable for logs.
Store the logs in Azure Cosmos DB with a JSON container.
A healthcare company stores sensitive patient data in Azure Data Lake Storage Gen2. They need to ensure that only authorized users can access data and that all access is audited. They also need to prevent data from being accessed by unauthorized Azure services. Which combination of security features should be used?
Use a private endpoint and Azure AD authentication, disable public access.
Use Azure RBAC and ACLs for authorization, enable firewall and virtual network service endpoints, and enable diagnostic settings for auditing.
Combination provides layered security and full audit.
Use managed identity for service access and disable public access.
Use Azure AD authentication and SAS tokens for access, enabling diagnostic logs for auditing.
Which TWO of the following are supported storage options for use as a source in Azure Synapse Pipeline Copy Activity?
Azure Data Lake Storage Gen2
ADLS Gen2 is a supported source.
Azure Analysis Services
Azure Cognitive Search
Azure Purview
Azure Blob Storage
Azure Blob Storage is a supported source.
You are reviewing a copy job configuration in Azure Data Factory that copies Parquet files from Azure Data Lake Storage Gen2 to Azure Synapse Analytics. The exhibit shows the job settings. If the source folder contains a file that is not in Parquet format (e.g., a CSV file), what will happen?
The copy job will skip the CSV file and stop.
The copy job will fail with an error.
The copy job will skip the CSV file and continue copying other Parquet files.
skipIncompatibleFiles=true causes skipping non-Parquet files.
The copy job will attempt to read the CSV file as Parquet and may produce corrupt data.
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Practice this domain46% of exam · 6 sample questions below
You are designing a batch processing solution using Azure Databricks. The data source is a large Parquet dataset stored in Azure Data Lake Storage Gen2 (ADLS Gen2). The processing requires joining two datasets: one with 10 billion rows and another with 1 million rows. The cluster uses Photon runtime. Which optimization should you apply to minimize shuffle?
Broadcast the smaller table (1 million rows) to all worker nodes.
Broadcasting the smaller table avoids shuffling the large table, significantly reducing data movement.
Increase the cluster size to reduce shuffle overhead.
Create bucketed tables on the join key for both datasets.
Use Delta Lake and optimize file layout with OPTIMIZE command.
You are running a Spark job in Azure Synapse Analytics that reads from a Delta Lake table and performs multiple transformations. The job fails with an out-of-memory error on the executors. Which action should you take first to resolve the issue?
Enable checkpointing to truncate the lineage.
Decrease the number of partitions to reduce overhead.
Increase the executor memory setting in the Spark configuration.
Increasing executor memory provides more heap space to avoid OOM errors.
Use the cache() action on intermediate DataFrames.
You are designing a data pipeline in Azure Data Factory (ADF) that copies data from an on-premises SQL Server database to Azure Synapse Analytics dedicated SQL pool. The pipeline must run daily and handle incremental loads efficiently. Which sink dataset type and copy method should you use?
Use Azure Synapse Analytics dedicated SQL pool as the sink dataset and use the Copy activity with PolyBase enabled.
Use Azure Synapse Analytics dedicated SQL pool as the sink dataset and enable the built-in Upsert option.
Use Azure Blob Storage as the sink dataset, then use PolyBase to load into the dedicated SQL pool.
Use Azure Synapse Analytics dedicated SQL pool as the sink dataset and use Stored Procedure with staging table and PolyBase.
This combination enables high-throughput ingestion and supports incremental loading via merge logic in the stored procedure.
You are implementing a streaming solution using Azure Stream Analytics. The input is from an IoT Hub receiving telemetry from thousands of devices. The output is to Azure Synapse Analytics dedicated SQL pool. The requirement is to compute rolling averages over a 5-minute tumbling window and write results every minute. Which windowing function and output configuration should you use?
Use a TumblingWindow with duration of 5 minutes and output every 5 minutes.
Use a SlidingWindow with duration 5 minutes and output every 1 minute.
Use a HoppingWindow with size 5 minutes and hop 1 minute.
Hopping windows with a 1-minute hop produce results every minute, each covering the last 5 minutes.
Use a SessionWindow with timeout 5 minutes and maximum duration 10 minutes.
You are optimizing a Spark DataFrame transformation in Azure Synapse Analytics. The DataFrame has 20 columns and 100 million rows. You notice that the job is slow due to many small files being written to the output. Which two actions can you take to reduce the number of output files? (Choose two.)
Use coalesce() to reduce the number of partitions without a shuffle.
Coalesce reduces partitions and thus output files, minimizing shuffle.
Enable caching on the DataFrame before writing.
Apply bucketing on a column to group data.
Increase the number of partitions using repartition() with a larger number.
Use repartition() with a smaller number of partitions.
Fewer partitions mean fewer files written.
You are designing a data processing solution using Azure Databricks. The data is stored in Delta Lake format. You need to ensure that when you read the latest version of the table, you only see committed data and not uncommitted transactions. Which isolation level should you use?
WriteSerializable
Serializable
ReadUncommitted
SnapshotIsolation
Delta Lake uses Snapshot isolation to read the latest committed version.
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Practice this domainThe DP-203 exam has 50 questions and must be completed in 120 minutes. The passing score is 700/1000.
Scenario-based questions covering exam objectives with detailed answer explanations.
The exam covers 3 domains: Secure, monitor, and optimize data storage and data processing, Design and implement data storage, Develop data processing. Questions are weighted by domain — higher-weight domains appear more on your actual exam.
No. These are original exam-style practice questions written against the official Microsoft DP-203 exam objectives. They are not copied from the real exam. Courseiva focuses on genuine understanding, not memorisation of braindumps.
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