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

Question 1

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?

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

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 2

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 3

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 4

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.

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Azure Data Explorer

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Azure Stream Analytics

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Azure Analysis Services

Question 5

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.

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Blob soft delete is enabled

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Versioning is enabled for blobs

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Geo-redundant storage is configured

Question 6

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 7

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

Question 8

A company wants to build a real-time dashboard that visualizes sales data as transactions occur. Which combination of Azure services should they use?

Accepted Answer

Azure Stream Analytics and Power BI. Azure Stream Analytics is a real-time event processing engine that can ingest streaming data (e.g., from Azure Event Hubs or IoT Hub) and output results directly to Power BI via the built-in Power BI output sink. This combination enables a live dashboard that updates automatically as sales transactions occur, without requiring batch processing or manual refresh.

Answer

Azure Synapse Analytics and PolyBase

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Azure Data Explorer and Azure Data Lake Storage

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Azure Analysis Services and Excel

Question 9

A data scientist needs to train a machine learning model using data stored in Azure Data Lake Storage. They want to use a collaborative notebook environment with built-in experiment tracking. Which Azure service should they use?

Accepted Answer

Azure Machine Learning. Azure Machine Learning provides a collaborative notebook environment (Jupyter notebooks) with built-in experiment tracking, model management, and automated ML capabilities. It is the correct choice for training machine learning models with data from Azure Data Lake Storage while tracking experiments.

Answer

Azure Synapse Analytics

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Azure Databricks

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Azure Data Studio

Question 10

An organization has a large dataset stored in Azure Blob Storage. They need to run complex analytics using SQL queries and also want to use the same data for machine learning models. Which Azure service provides both SQL-based analytics and native integration with ML frameworks?

Accepted Answer

Azure Synapse Analytics. Azure Synapse Analytics is correct because it provides a unified analytics platform that combines enterprise data warehousing with big data analytics. It offers built-in SQL-based querying via dedicated SQL pools or serverless SQL pools, and it natively integrates with machine learning frameworks like Apache Spark and Azure Machine Learning for building and training models on the same data stored in Azure Blob Storage.

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Azure Data Factory

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Azure Analysis Services

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Azure SQL Database

Question 11

A company wants to provide self-service analytics to business users, allowing them to create reports and dashboards from data stored in Azure Data Lake Storage. Which tool should they use?

Accepted Answer

Power BI. Power BI is the correct tool because it provides self-service analytics capabilities, allowing business users to connect to data stored in Azure Data Lake Storage, create interactive reports and dashboards, and share insights without requiring deep technical skills. Options A, B, and D are incorrect: Azure Synapse Studio is a big data and data warehousing tool, not designed for self-service business user dashboard creation; Azure Machine Learning studio is for building, training, and deploying machine learning models, not for creating reports; Azure Data Studio is a database management and query tool, not a reporting tool.

Answer

Azure Synapse Studio

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Azure Machine Learning studio

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Azure Data Studio

Question 12

An organization has a data lake that contains both structured and unstructured data. They need to catalog the data assets and enable data discovery for users. Which Azure service should they use?

Accepted Answer

Microsoft Purview. Microsoft Purview is a unified data governance service that helps you manage and govern your on-premises, multicloud, and software-as-a-service (SaaS) data. It provides automated data discovery, sensitive data classification, and end-to-end data lineage, making it the correct choice for cataloging both structured and unstructured data assets in a data lake and enabling data discovery for users.

Answer

Azure Data Factory

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Azure Synapse Analytics

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Azure Data Lake Storage

Question 13

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.

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Azure Analysis Services

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Azure SQL Database

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Azure Data Lake Storage

Question 14

A company runs a SQL Server database on an Azure virtual machine. They need to offload reporting queries to a read-only copy without modifying the application. Which Azure service should they use?

Accepted Answer

Azure SQL Database with read scale-out. Azure SQL Database with read scale-out (C) is correct because it creates a read-only replica of the database that can handle reporting queries without modifying the application. The application simply adds `ApplicationIntent=ReadOnly` to the connection string, and the Azure gateway automatically routes read-only queries to the secondary replica, offloading the primary from reporting workloads.

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Azure Analysis Services

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Azure SQL Managed Instance

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Azure Synapse Analytics dedicated SQL pool

Question 15

A data engineer needs to transform and clean data from multiple sources before loading it into Azure Synapse Analytics. Which Azure service should they use for this ETL process?

Accepted Answer

Azure Data Factory. Azure Data Factory is the correct service because it is a cloud-based ETL (Extract, Transform, Load) service designed specifically to orchestrate and automate data movement and transformation from multiple sources. It provides built-in connectors for various data stores and supports data flows for cleaning and transforming data before loading it into Azure Synapse Analytics.

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Azure Analysis Services

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Azure Databricks

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Azure Stream Analytics