DP-900 Practice Test 34 — 15 Questions

Question 1

A company uses Azure Stream Analytics to process IoT data from thousands of devices. The output is written to Azure SQL Database for reporting. Recently, the job latency increased significantly. The company suspects that the SQL Database is throttling writes. Which action should the company take to reduce latency?

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

Accepted Answer

Switch the output to Azure Cosmos DB with sufficient RU/s and use change feed to sync to SQL Database.. The latency is caused by Azure SQL Database throttling writes due to its row-based storage and limited write throughput. By switching the output to Azure Cosmos DB with sufficient Request Units per second (RU/s), the Stream Analytics job can write at high speed without throttling, and the change feed can then asynchronously sync data to Azure SQL Database for reporting, decoupling the write bottleneck.

Answer

Change the input serialization from JSON to Avro.

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Increase the batch size of writes to Azure SQL Database.

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Increase the number of Streaming Units for the Stream Analytics job.

Question 2

The exhibit shows a KQL query in Azure Data Explorer. What is the output of this query?

Accepted Answer

Top 5 states by total property damage. The KQL query uses `summarize` to aggregate total property damage by state, then `top 5 by total_property_damage` to return the five states with the highest total damage. The `desc` argument (default) orders the results in descending order, making option B correct.

Answer

Bottom 5 states by total property damage

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All states with total property damage

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All storm events after 2024-01-01

Question 3

A multinational corporation needs to store archival data for 10 years with the lowest possible storage cost, while still being able to retrieve it within 24 hours if needed. Which Azure storage tier should they use?

Accepted Answer

Archive Blob Storage. Archive Blob Storage is the correct choice because it is designed for long-term retention of data that is rarely accessed, offering the lowest storage cost among Azure blob tiers. The 10-year retention requirement and 24-hour retrieval window align perfectly with Archive's capabilities, as data can be rehydrated to a hot or cool tier within hours (typically up to 15 hours for standard priority rehydration).

Answer

Cool Blob Storage

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Premium Blob Storage

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Hot Blob Storage

Question 4

A startup is building a web application with a relational database backend. They expect variable traffic and want to minimize costs by scaling the database automatically based on demand. Which Azure service should they use?

Accepted Answer

Azure SQL Database serverless. Azure SQL Database serverless is the correct choice because it automatically scales compute resources based on demand and pauses the database during idle periods, charging only for storage and minimal compute. This aligns with the startup's need for variable traffic and cost minimization, as it eliminates the need to provision for peak capacity manually.

Answer

Azure SQL Managed Instance

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SQL Server on Azure Virtual Machines

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Azure Database for MariaDB

Question 5

Refer to the exhibit. You are deploying an Azure Storage account. The JSON snippet represents a template parameter. What does the 'isHnsEnabled' property enable?

Accepted Answer

Hierarchical namespace for the storage account. The 'isHnsEnabled' property enables the hierarchical namespace for the storage account, which is a core feature of Azure Data Lake Storage Gen2. When set to true, it allows the storage account to organize blobs into a directory hierarchy, enabling POSIX-like access control lists (ACLs) and file system semantics. This is essential for big data analytics workloads that require a file system structure rather than a flat blob storage model.

Answer

Blob versioning

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Soft delete for blobs

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Geo-redundant storage

Question 6

A company is designing a data solution for a retail application. The solution must support real-time analytics on streaming sales data, and also provide historical reports for business intelligence. Which TWO data processing models should be combined to meet these requirements?

Accepted Answer

Batch processing. Batch processing (B) is correct because it is used to process large volumes of historical sales data at scheduled intervals, enabling the generation of comprehensive business intelligence reports. Stream processing (E) is correct because it handles real-time data ingestion and analytics on streaming sales data, allowing the application to react instantly to sales events. Combining these two models (often called a Lambda architecture) meets both the real-time and historical reporting requirements.

Answer

Distributed processing

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Data lake storage

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Transactional database

Question 7

A company uses Azure SQL Database with geo-replication for disaster recovery. During a regional outage, they manually failover to the secondary region. After the primary region is restored, they need to re-establish geo-replication with minimal downtime. What should they do?

Accepted Answer

Initiate a planned failover to switch back to the original region. After a manual failover to the secondary region, the original primary becomes a secondary database. To re-establish geo-replication with minimal downtime, you should initiate a planned failover (also called a graceful failover) to switch back to the original region. This operation reverses the roles without data loss and avoids the need to reseed the database, keeping downtime to seconds.

Answer

Drop the secondary database and create a new one

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Delete the geo-replication link and create a new one

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Manually swap the roles of the primary and secondary

Question 8

A marketing team needs to analyze customer sentiment from social media posts in real time. The solution must ingest a stream of tweets, perform sentiment analysis using a pre-built AI model, and store the results in a dashboard for immediate visualization. The team has limited coding experience and prefers a low-code/no-code approach. Which combination of Azure services should you recommend?

Accepted Answer

Azure Event Hubs, Azure Stream Analytics, and Power BI. Azure Event Hubs ingests the real-time tweet stream, Azure Stream Analytics performs sentiment analysis using its built-in machine learning functions (a low-code/no-code approach), and Power BI provides the dashboard for immediate visualization. This combination meets the real-time, low-code requirement without custom coding.

Answer

Azure Event Hubs, Azure Functions, and Azure Cosmos DB

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Azure IoT Hub, Azure Data Factory, and Power BI

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Azure Event Hubs, Azure HDInsight, and Power BI

Question 9

Your company is implementing a data governance solution using Microsoft Purview. The data catalog must automatically scan and classify sensitive data in Azure SQL Database, Azure Synapse Analytics, and Amazon S3. The company uses Microsoft Entra ID for identity management. You need to ensure that the Purview managed identity can authenticate to these data sources. Which authentication method should you configure for the Amazon S3 connection?

Accepted Answer

AWS IAM authentication. Amazon S3 is an external cloud storage service that does not support Microsoft Entra ID, SQL Authentication, or Windows Authentication. To authenticate Purview's managed identity to S3, you must configure AWS IAM authentication, which allows Purview to assume an IAM role with permissions to read the S3 bucket metadata and data for scanning and classification.

Answer

SQL Authentication

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Windows Authentication

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Microsoft Entra ID authentication

Question 10

A financial services company needs to run ad-hoc SQL queries on petabytes of data stored in Azure Data Lake Storage without provisioning a dedicated data warehouse. Which Azure service should they use?

Accepted Answer

Azure Synapse Analytics serverless SQL pool. Azure Synapse Analytics serverless SQL pool is the correct choice because it allows you to run ad-hoc SQL queries directly against data in Azure Data Lake Storage without provisioning any dedicated compute resources. It uses a pay-per-query model, automatically scaling compute to handle petabytes of data, making it ideal for intermittent, exploratory workloads.

Answer

Azure Analysis Services

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Azure SQL Database

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Azure Data Lake Storage

Question 11

A startup wants to build a new web application with a relational database. They expect variable traffic and want to minimize costs by paying only for the compute resources they use. Which Azure SQL Database deployment option should they choose?

Accepted Answer

Serverless compute tier. The Serverless compute tier for Azure SQL Database automatically pauses the database during periods of inactivity and resumes it when traffic returns, charging only for the compute resources consumed. This makes it ideal for a startup with variable traffic that wants to minimize costs by paying only for what they use.

Answer

Provisioned compute tier

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Elastic pool

Answer

SQL Server on Azure Virtual Machines

Question 12

A company needs to migrate a large on-premises SQL Server database to Azure. The migration must have minimal downtime and support ongoing replication. Which Azure service should they use?

Accepted Answer

Azure Database Migration Service. Azure Database Migration Service (DMS) is designed for online migrations with minimal downtime, supporting ongoing replication from SQL Server to Azure SQL Database. It uses the Data Migration Assistant (DMA) for assessment and the Azure DMS for continuous sync, enabling near-zero downtime during cutover.

Answer

Azure Data Box

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Azure Data Factory

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Azure SQL Database

Question 13

A company stores customer orders in an Azure SQL Database. They need to ensure that the database can automatically scale to handle peak loads without manual intervention. Which Azure feature should they use?

Accepted Answer

Enable the serverless compute tier. The serverless compute tier for Azure SQL Database automatically pauses and resumes the database based on compute usage, scaling compute resources on demand without manual intervention. This makes it ideal for handling unpredictable peak loads while minimizing costs during idle periods.

Answer

Purchase reserved capacity

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Add a read replica

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Configure an elastic pool

Question 14

Your company uses Azure Synapse Analytics to run analytical queries on large datasets. You need to ensure that queries against a frequently accessed fact table perform well without impacting other workloads. Which feature should you use?

Accepted Answer

Enable result set caching for the database.. Result set caching stores query results in the Synapse SQL pool's cache, so repeated queries against the fact table return cached results instantly without re-scanning data. This ensures fast performance for frequently accessed queries while isolating resource usage from other workloads, as cached results do not consume concurrency slots or I/O resources.

Answer

Create materialized views on the fact table.

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Partition the fact table by a frequently filtered column.

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Use workload classification to prioritize the queries.

Question 15

A company uses Azure Synapse Analytics to run large-scale data transformations. They need to optimize costs for predictable workloads that run every night. Which Azure feature should they configure?

Accepted Answer

Implement dedicated SQL pool pause and resume. Azure Synapse Analytics dedicated SQL pool supports pause and resume, which stops compute billing while preserving data in storage. For predictable nightly workloads, pausing the pool during idle hours eliminates compute costs, then resuming it before the job runs. This directly optimizes cost for scheduled, non-continuous workloads.

Answer

Enable always-on availability

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Enable data compression on tables

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Configure auto-scale