DP-900 Practice Test 18 — 15 Questions

Question 1

Refer to the exhibit. A data engineer is reviewing an ARM template for a storage account. What does the property 'isHnsEnabled' set to true indicate?

Accepted Answer

The storage account supports Azure Data Lake Storage Gen2. The 'isHnsEnabled' property, when set to true, enables the Hierarchical Namespace (HNS) on the storage account. HNS is the core feature that differentiates Azure Data Lake Storage Gen2 from a standard blob storage account, allowing for a true file system hierarchy with POSIX-like access control lists (ACLs). This enables the storage account to support Data Lake Storage Gen2 workloads.

Answer

Blob soft delete is enabled

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Versioning is enabled for blobs

Answer

Geo-redundant storage is configured

Question 2

Refer to the exhibit. You deploy this Azure Stream Analytics job. The job runs but no data is written to the Azure SQL Database table. What is the most likely cause?

Accepted Answer

The TumblingWindow has not yet elapsed. The TumblingWindow function in Azure Stream Analytics processes data in fixed, non-overlapping time intervals. Since the job runs but no data is written, the most likely cause is that the first window has not yet elapsed, meaning no aggregation has been triggered to output results. Stream Analytics only emits results when a tumbling window completes, so data will not appear in the SQL Database until the window duration passes.

Answer

The query syntax is invalid

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The Event Hub name is incorrect

Answer

The SKU does not support SQL output

Question 3

A manufacturing company ingests real-time sensor data from assembly line machines into Azure Event Hubs. The company needs to calculate a 5-minute rolling average of temperature readings for each machine and compare it against a static threshold value stored in a CSV file in Azure Blob Storage. If the average exceeds the threshold, an alert must be triggered. Which Azure service should be used for this real-time data processing?

Accepted Answer

Azure Stream Analytics. Azure Stream Analytics is the correct choice because it is designed for real-time stream processing, including windowed aggregations like a 5-minute rolling average. It can directly ingest data from Azure Event Hubs, perform the calculation using a TumblingWindow or HoppingWindow function, and reference static data (the threshold CSV) from Azure Blob Storage via a reference data input. If the computed average exceeds the threshold, Stream Analytics can output the alert to a sink like Azure Functions or a notification service.

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Azure Data Factory

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Azure Synapse Analytics

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Azure HDInsight

Question 4

Your company uses Azure SQL Database to power a global application. You need to ensure that users in Europe and Asia have low-latency read access to product data, while writes are synchronized across all regions. What should you configure?

Accepted Answer

Configure Active Geo-Replication with readable secondaries in Europe and Asia.. Active Geo-Replication for Azure SQL Database allows you to configure readable secondary replicas in different Azure regions. This provides low-latency read access for users in Europe and Asia by directing their read traffic to the nearest secondary, while writes are synchronized asynchronously to all secondaries, ensuring data consistency across regions.

Answer

Use Azure Traffic Manager to route users to the nearest Azure SQL Database instance.

Answer

Migrate to Azure Cosmos DB for multi-region writes.

Answer

Create a failover group that includes all regions.

Question 5

A retail company collects sales data from multiple stores. Data is ingested into Azure Data Lake Storage Gen2 as CSV files. The data team needs to run ad-hoc SQL queries on this data without moving it, and they want to pay only for the amount of data processed. They also need to integrate with Power BI for visualization. Which Azure service should they use?

Accepted Answer

Azure Synapse Serverless SQL pool. Azure Synapse Serverless SQL pool (option D) is correct because it allows querying data directly from Azure Data Lake Storage Gen2 using T-SQL without moving the data, and it uses a pay-per-query model where you are billed only for the amount of data processed. It also integrates seamlessly with Power BI for visualization, making it ideal for ad-hoc SQL queries on CSV files.

Answer

Azure Synapse Analytics dedicated SQL pool

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Azure SQL Database

Answer

Azure Data Lake Analytics

Question 6

Your organization is migrating on-premises SQL Server databases to Azure. The databases include a mission-critical OLTP system that requires high availability with automatic failover and a reporting database that is used for read-only queries. You need to choose the appropriate Azure SQL deployment options for each workload. The OLTP system must have a recovery point objective (RPO) of less than 5 seconds and a recovery time objective (RTO) of less than 30 seconds. The reporting database should be cost-effective and can tolerate up to 5 minutes of data loss. What should you recommend?

Accepted Answer

Use Azure SQL Database Managed Instance with a failover group for OLTP, and use a read-only replica of the Managed Instance for reporting.. Azure SQL Database Managed Instance supports failover groups that provide automatic failover across regions with an RPO of less than 5 seconds and an RTO of less than 30 seconds, meeting the OLTP requirements. The read-only replica of the Managed Instance can be used for reporting queries without impacting the primary OLTP workload, and it is cost-effective as it does not require a separate database instance.

Answer

Use SQL Server on Azure Virtual Machines with Always On Availability Groups for both workloads.

Answer

Use Azure SQL Database Hyperscale for OLTP and Azure SQL Database serverless for reporting.

Answer

Use Azure SQL Database single database with active geo-replication for both workloads.

Question 7

A multinational corporation uses Azure Data Factory to orchestrate data pipelines across multiple regions. The company notices that pipeline runs in the West Europe region consistently fail due to throttling errors from the source database. The source database is an Azure SQL Database in the same region. The company needs to reduce throttling while maintaining pipeline throughput. What should the company do?

Accepted Answer

Configure auto-scale on the Azure SQL Database to handle higher load.. The throttling errors originate from the Azure SQL Database source, which has resource limits (DTU or vCore-based). Configuring auto-scale on the Azure SQL Database dynamically adjusts its performance tier to handle higher concurrency and throughput, directly addressing the root cause of throttling while maintaining pipeline throughput. This aligns with the requirement to reduce throttling without reducing workload.

Answer

Increase the maximum number of Data Factory activity retries.

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Stage extracted data in Azure Blob Storage before loading into the destination.

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Use a self-hosted integration runtime in the same region to execute pipelines.

Question 8

A retail company captures real-time sensor data from IoT devices to detect anomalies and predict equipment failures. The data must be processed immediately as it arrives. Which type of data processing workload best describes this scenario?

Accepted Answer

Streaming processing. B is correct because streaming processing is designed for continuous, real-time data ingestion and immediate analysis, which matches the requirement to process sensor data as it arrives. Technologies like Azure Stream Analytics or Apache Kafka enable low-latency processing of IoT data streams to detect anomalies and predict failures without batching.

Answer

Batch processing

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Online transaction processing (OLTP)

Answer

Data warehousing

Question 9

A data engineering team at a logistics company handles two distinct data processing workloads. The first workload ingests GPS data from delivery trucks every 10 seconds and updates a dashboard showing real-time vehicle locations. The second workload processes monthly CSV files of completed deliveries to generate reports on delivery times and route efficiency. Which statement correctly identifies these workloads?

Accepted Answer

GPS data processing is a streaming workload; monthly report processing is a batch workload. C is correct because GPS data ingested every 10 seconds is a continuous, near-real-time stream, making it a streaming workload. Monthly CSV file processing is a classic batch workload, as data is collected over a period and processed in a single, scheduled job. This distinction is fundamental in Azure data services: streaming workloads use services like Azure Stream Analytics or Event Hubs, while batch workloads use Azure Synapse Pipelines or Azure Data Factory.

Answer

Both workloads are streaming workloads

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GPS data processing is a batch workload; monthly report processing is a streaming workload

Answer

Both workloads are batch workloads

Question 10

A company plans to migrate a 500 GB SQL Server database from on-premises to Azure SQL Database. They require minimal downtime during the migration. Which approach should they use?

Accepted Answer

Use Azure Database Migration Service with online migration mode. Azure Database Migration Service (DMS) with online migration mode is the correct approach because it supports minimal-downtime migrations by continuously replicating ongoing changes from the source SQL Server to Azure SQL Database using the transactional replication technology. This allows the source database to remain operational during the migration, and only a brief cutover is needed at the end to switch applications to the target.

Answer

Export a BACPAC file and import to Azure SQL Database

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Use Azure Site Recovery to replicate the database

Answer

Create a full database backup and restore to Azure SQL Database

Question 11

Refer to the exhibit. The JSON shows a configuration for which Azure service?

Accepted Answer

Azure Data Factory. The JSON snippet defines a pipeline with a copy activity that moves data from a source (Azure Blob Storage) to a sink (Azure SQL Database). This is the core pattern of Azure Data Factory (ADF), which orchestrates and automates data movement and transformation. The structure with 'name', 'properties', 'activities', 'typeProperties', 'source', and 'sink' is specific to ADF pipeline definitions.

Answer

Azure Analysis Services

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Power BI

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Azure Synapse Analytics

Question 12

A company uses Azure SQL Database for a financial system. The Transactions table contains millions of rows with a TransactionDate column. Queries frequently aggregate sales totals for the current month, but historical data must be retained for 7 years. Currently, queries scan the entire table, causing performance issues. The company also wants to simplify archiving of old data. Which design should they implement?

Accepted Answer

Implement table partitioning by month on TransactionDate.. Table partitioning by month on TransactionDate allows Azure SQL Database to efficiently manage and query large tables by splitting data into manageable segments. Queries that filter on TransactionDate for the current month will only scan the relevant partition(s), eliminating full table scans. Additionally, partitioning simplifies archiving by enabling swift partition switching to move old data to archive tables without complex ETL processes.

Answer

Create a non-clustered index on the TransactionDate column.

Answer

Create a materialized view for the current month's data.

Answer

Convert the table to use a clustered columnstore index.

Question 13

Your organization wants to run SQL queries on data stored in Azure Blob Storage without moving the data. Which Azure service supports this?

Accepted Answer

Azure Synapse Serverless SQL pool. Azure Synapse Serverless SQL pool allows you to query data directly from Azure Blob Storage using T-SQL without moving the data. It uses a distributed query engine that reads files in place, supporting formats like Parquet, CSV, and JSON, making it ideal for ad-hoc analytics on stored data.

Answer

Azure SQL Database

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Azure Analysis Services

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Azure Data Lake Storage Gen2

Question 14

You need to choose a data store for a mobile app that requires real-time synchronization of user preferences across devices. The data is small per user and key-value oriented. Which Azure service is most appropriate?

Accepted Answer

Azure Cosmos DB. Azure Cosmos DB is the most appropriate choice because it provides global distribution, low-latency reads and writes, and automatic conflict resolution, which are essential for real-time synchronization of user preferences across devices. Its key-value API (e.g., Table API or Core SQL API with a simple partition key) efficiently handles small, per-user data with a key-value orientation, ensuring that changes made on one device are quickly reflected on others.

Answer

Azure Cache for Redis

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Azure Blob Storage

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Azure SQL Database

Question 15

Your company has a Power BI report that uses DirectQuery to Azure SQL Database. Users report that the report is slow when multiple users access it simultaneously. The database is underprovisioned. Which action should you take to improve performance without changing the report design?

Accepted Answer

Scale up the Azure SQL Database to a higher service tier.. The root cause is an underprovisioned Azure SQL Database, which cannot handle the concurrent query load from multiple Power BI users using DirectQuery. Scaling up to a higher service tier (e.g., from S2 to S3 or a DTU-based tier) increases the database's DTUs (Database Transaction Units), directly improving throughput and reducing query latency without altering the report design.

Answer

Enable query caching in Power BI Premium.

Answer

Change the report to use Import mode instead of DirectQuery.

Answer

Add indexes to the tables used in the report.