DP-900 Describe an analytics workload on Azure Practice Test 14 — 15 Questions

Question 1

An organization needs to run complex queries on petabytes of data stored in Azure Data Lake Storage. They want to use serverless compute to avoid managing infrastructure. Which Azure service should they use?

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

Accepted Answer

Azure Synapse Serverless SQL pool. Azure Synapse Serverless SQL pool is the correct choice because it provides serverless compute that can run complex T-SQL queries directly against data stored in Azure Data Lake Storage without requiring any infrastructure management. It uses a pay-per-query billing model and can scale automatically to handle petabytes of data, making it ideal for ad-hoc analytics on large-scale data lakes.

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Azure Analysis Services

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Azure HDInsight

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Azure SQL Database

Question 2

Refer to the exhibit. A data engineer runs the PowerShell script shown. What is the purpose of this script?

Accepted Answer

List blobs modified in the last 7 days. The script uses `Get-AzStorageBlob` with the `-Prefix` parameter to filter blobs by name, then applies a `Where-Object` filter to select only blobs whose `LastModified` property is greater than or equal to 7 days ago. This effectively lists blobs modified in the last 7 days. The script does not perform any copy or delete operations, and it does not list all blobs without filtering.

Answer

List all blobs in the container

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Copy blobs to another container

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Delete old blobs from the container

Question 3

A company uses Azure Stream Analytics to process IoT data from thousands of devices. They need to store the results in a way that supports fast querying for historical analysis. Which output sink should they use?

Accepted Answer

Azure Data Lake Storage Gen2. Azure Data Lake Storage Gen2 (ADLS Gen2) is the correct output sink because it combines a hierarchical namespace with Azure Blob Storage's scalable object storage, enabling fast querying for historical analysis via tools like Azure Synapse Analytics, PolyBase, or Apache Spark. ADLS Gen2 supports high-throughput writes from Stream Analytics and allows efficient directory-level operations and fine-grained access control, which are critical for large-scale IoT data analytics.

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Azure Table Storage

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Azure Blob Storage

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Azure Event Hubs

Question 4

A data analyst needs to create interactive reports from data stored in an Azure SQL Database. They want to use a self-service tool that requires minimal IT support. Which tool should they use?

Accepted Answer

Power BI Desktop. Power BI Desktop is a self-service business intelligence tool designed for creating interactive reports and dashboards with minimal IT support. It connects directly to Azure SQL Database, allowing analysts to import or query data using DirectQuery, and provides drag-and-drop visualizations without requiring database administration skills.

Answer

Azure Synapse Studio

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SQL Server Management Studio

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Azure Data Studio

Question 5

Refer to the exhibit. An Azure Data Factory pipeline JSON is shown. What does this pipeline do?

Accepted Answer

Copies filtered sales data from on-premises to Azure SQL Database. The pipeline uses a Copy activity with a source dataset pointing to an on-premises SQL Server (via a self-hosted integration runtime) and a sink dataset pointing to an Azure SQL Database. The source query includes a WHERE clause filtering sales data by a date range, so only filtered data is copied. This matches option C.

Answer

Copies sales data from Azure SQL Database to on-premises

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Copies all sales data from on-premises to Azure SQL Database

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Copies sales data from on-premises to Azure Data Lake Storage

Question 6

Which THREE are benefits of using a data warehouse in Azure?

Accepted Answer

Optimizes query performance for analytical workloads. A data warehouse in Azure (e.g., Azure Synapse Analytics) is optimized for analytical workloads through columnar storage and massively parallel processing (MPP), which significantly improves query performance on large datasets. This architecture is designed for read-heavy, aggregation-based queries typical of business intelligence and reporting, not for transactional or real-time operations.

Answer

Stores unstructured data like videos

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Enables real-time streaming analytics

Question 7

A company uses Azure Databricks for data engineering. They need to ensure that only authorized users can access the workspace, and they want to use single sign-on (SSO) with their existing identity provider. Which integration should they configure?

Accepted Answer

Microsoft Entra ID (Azure AD). Microsoft Entra ID (Azure AD) is the identity and access management service that provides SSO capabilities for Azure Databricks. By integrating Azure Databricks with Entra ID, you can enforce conditional access policies and authenticate users via your existing identity provider using protocols like SAML 2.0 or OAuth 2.0, ensuring only authorized users access the workspace.

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Microsoft Defender XDR

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Microsoft Intune

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Azure Key Vault

Question 8

A company plans to implement a near-real-time analytics solution for streaming IoT sensor data. Which Azure service should they use to ingest and process the data streams?

Accepted Answer

Azure Stream Analytics. Azure Stream Analytics is a real-time event processing engine designed to ingest, process, and analyze high-velocity streaming data from sources like IoT sensors. It supports SQL-based queries to transform and route data streams to outputs such as Power BI or Azure Synapse, making it ideal for near-real-time analytics.

Answer

Azure Data Factory

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Azure Synapse Analytics

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Azure Data Lake Storage Gen2

Question 9

A data engineer needs to build a data pipeline that runs daily to copy sales data from an on-premises SQL Server to Azure Synapse Analytics. Which Azure service should they use to orchestrate the pipeline?

Accepted Answer

Azure Data Factory. Azure Data Factory (ADF) is the correct choice because it is a cloud-based data integration service specifically designed to orchestrate and automate data pipelines. It supports scheduled triggers (e.g., daily runs) and provides native connectors to copy data from on-premises SQL Server (via Self-Hosted Integration Runtime) to Azure Synapse Analytics, making it the ideal tool for this ETL/ELT workload.

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Azure Analysis Services

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Azure Databricks

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Azure HDInsight

Question 10

A company uses Azure Synapse Analytics for its data warehouse. They notice that query performance is degrading over time as data grows. Which action would most likely improve performance without requiring additional compute resources?

Accepted Answer

Partition large tables based on date or other high-cardinality columns. Partitioning large tables on a high-cardinality column like date enables partition elimination, where queries only scan relevant partitions instead of the entire table. This reduces I/O and improves performance without requiring additional compute resources, as it optimizes data access patterns within the existing Synapse SQL pool.

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Migrate to a star schema on a separate Azure SQL Database

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Increase the Synapse SQL pool service level

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Remove columnstore indexes from large tables

Question 11

Which THREE components are essential for building a modern data warehouse architecture on Azure?

Accepted Answer

Azure Databricks. Azure Databricks is correct because it provides an Apache Spark-based analytics platform that enables data engineering, data science, and machine learning on large-scale data. In a modern data warehouse architecture, Azure Databricks is used for data transformation, preparation, and advanced analytics, often feeding into or complementing Azure Synapse Analytics for structured querying and reporting.

Answer

Azure Analysis Services

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Azure Cosmos DB

Question 12

Which TWO Azure services are designed for big data batch processing?

Accepted Answer

Azure Databricks. Azure Databricks is correct because it provides an Apache Spark-based analytics platform optimized for batch processing large datasets, enabling ETL, data transformation, and machine learning at scale. It uses distributed computing to process data in parallel across clusters, making it ideal for big data batch workloads.

Azure HDInsight is also correct as it is a managed, full-spectrum, open-source analytics service for enterprises. It allows you to run popular open-source frameworks like Hadoop (for MapReduce batch processing), Spark (for batch and interactive processing), Hive, and others on Azure, making it suitable for big data batch processing scenarios.

Answer

Azure Data Explorer

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Azure Stream Analytics

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Azure Analysis Services

Question 13

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

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Geo-redundant storage is configured

Question 14

Refer to the exhibit. An analyst runs this Kusto Query Language (KQL) query in Azure Data Explorer. What is the primary purpose of this query?

Accepted Answer

Find the top 5 most common event types in Texas. The query uses the `summarize` operator with `count()` to count events per `EventType`, then `top 5 by count_` to return the five event types with the highest counts, filtered to only rows where `State == 'TEXAS'`. This directly finds the top 5 most common event types in Texas.

Answer

Calculate total damage in Texas

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Identify events with the highest damage

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List all storm events in Texas

Question 15

Refer to the exhibit. A developer is creating an ARM template for an Azure Synapse workspace. What is the purpose of the 'defaultDataLakeStorage' property?

Accepted Answer

Defines the primary storage account for the workspace. The 'defaultDataLakeStorage' property in an ARM template for Azure Synapse Analytics defines the primary Azure Data Lake Storage Gen2 account that the workspace uses as its default storage. This storage account is where the workspace stores its data, including the data lake files and the metadata for the SQL and Spark engines. It is essential for the workspace to function, as it provides the underlying storage for tables, pipelines, and other workspace assets.

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Sets the location for pipeline execution history

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Specifies the storage account for Apache Spark logs

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Configures the storage for SQL pool backups