DP-700 Practice Questions and Answers Part 2: Microsoft Fabric Exam Prep

Welcome to Part 2 of our DP-700 practice questions and answers series. This post includes questions 11–20 for the Microsoft DP-700: Implementing Data Engineering Solutions Using Microsoft Fabric exam.

In this set, you will practice important exam topics such as Fabric deployment pipelines, eventhouse deployment, warehouse validation, OneLake availability, Azure DevOps integration, managed private endpoints, shortcut caching, orchestration patterns, domains, and workspace roles.

DP-700 Practice Questions and Answers – Part 2

Question 11: Understanding Deployment Pipeline Behavior

You have a Fabric workspace named Workspace1_DEV that contains the following items:

• 10 reports
• Four notebooks
• Three lakehouses
• Two data pipelines
• Two Dataflow Gen1 dataflows
• Three Dataflow Gen2 dataflows
• Five semantic models, each with a scheduled refresh policy

You create a deployment pipeline named Pipeline1 to move items from Workspace1_DEV to a new workspace named Workspace1_TEST. You deploy all items from Workspace1_DEV to Workspace1_TEST.

For each statement, select whether it is true or false:

• Data from the semantic models will be deployed to the target stage.
• The Dataflow Gen1 dataflows will be deployed to the target stage.
• The scheduled refresh policies will be deployed to the target stage.

Correct Answer: No / Yes / No

Explanation

When items are deployed through a Fabric deployment pipeline, the deployment usually moves item definitions, metadata, and supported configuration. It does not copy the actual data stored in semantic models.

Semantic model data is not deployed to the target stage. The target semantic model must be refreshed after deployment to load data.

Dataflow Gen1 dataflows can be deployed as supported Fabric items, so they are moved to the target stage.

Scheduled refresh policies are not automatically transferred as active refresh schedules. These usually need to be configured again in the target environment.

Question 12: Deploying an Eventhouse Across Environments

You have a Fabric deployment pipeline that uses three workspaces named Dev, Test, and Prod.

You need to deploy an eventhouse as part of the deployment process. What should you use to add the eventhouse to the deployment process?

1. GitHub Actions
2. A deployment pipeline
3. An Azure DevOps pipeline

Correct Answer: B. A deployment pipeline

Explanation

A Fabric deployment pipeline is designed to move supported Fabric items between lifecycle stages such as Dev, Test, and Prod. It is the native Fabric feature for promoting items across environments.

GitHub Actions and Azure DevOps pipelines can help automate CI/CD workflows, but the Fabric deployment pipeline is the correct item for adding and promoting Fabric content such as an eventhouse through deployment stages.

Question 13: Validating a Warehouse Before Deployment

You have a Fabric workspace named Workspace1 that contains a warehouse named Warehouse1.

You plan to deploy Warehouse1 to a new workspace named Workspace2. As part of the deployment process, you need to verify whether Warehouse1 contains invalid references. The solution must minimize development effort.

What should you use?

1. A database project
2. A deployment pipeline
3. A Python script
4. A T-SQL script

Correct Answer: B. A deployment pipeline

Explanation

A deployment pipeline provides built-in validation during deployment. It can detect issues such as invalid references or dependency problems when moving items from one workspace to another.

This approach minimizes development effort because you do not need to create custom scripts or manually inspect warehouse dependencies. A database project or script may provide deeper customization, but the question asks for the lowest-effort built-in option.

Question 14: OneLake Availability for Eventhouse Data

You have a Fabric workspace that contains a Real-Time Intelligence solution and an eventhouse. Users report that they cannot see the eventhouse data from OneLake file explorer.

You enable OneLake availability for the eventhouse. What will be copied to OneLake?

1. Only data added to new databases that are added to the eventhouse
2. Only the existing data in the eventhouse
3. No data
4. Both new data and existing data in the eventhouse
5. Only new data added to the eventhouse

Correct Answer: D. Both new data and existing data in the eventhouse

Explanation

When OneLake availability is enabled for an eventhouse, both existing data and new incoming data become available through OneLake. This allows users and tools such as OneLake file explorer to access the data more easily.

The feature is useful when eventhouse data needs to be exposed to broader Fabric workloads without requiring users to manually export or copy data separately.

Question 15: Authenticating Azure DevOps API Calls to Fabric

You have a Fabric workspace named Workspace1.

You plan to integrate Workspace1 with Azure DevOps. You will use a Fabric deployment pipeline named deployPipeline1 to deploy items from Workspace1 to higher environment workspaces as part of a medallion architecture. You will run deployPipeline1 by using an API call from an Azure DevOps pipeline.

You need to configure API authentication between Azure DevOps and Fabric. Which type of authentication should you use?

1. Service principal
2. Microsoft Entra username and password
3. Managed private endpoint
4. Workspace identity

Correct Answer: A. Service principal

Explanation

A service principal is the correct option for automated authentication between Azure DevOps and Fabric APIs. It provides an application identity that can be granted specific permissions and used securely in automation workflows.

Using a username and password is not recommended for secure automation. A managed private endpoint is used for private network connectivity, not API authentication. A workspace identity is useful for workspace-level resource access but is not the correct choice for Azure DevOps API authentication in this scenario.

Question 16: Shortcut Cache Behavior in Microsoft Fabric

You have a Google Cloud Storage container named storage1 that contains files such as ProductFile, StoreFile, and TripsFile. A Fabric workspace named Workspace1 has shortcut caching enabled and contains a lakehouse named Lakehouse1.

Lakehouse1 has shortcuts named:

• Products
• Stores
• Trips

You need to read data from all shortcuts. Which shortcuts will retrieve data from the cache?

1. Stores only
2. Products only
3. Stores and Products only
4. Products, Stores, and Trips
5. Trips only
6. Products and Trips only

Correct Answer: C. Stores and Products only

Explanation

When shortcut caching is enabled in Microsoft Fabric, eligible shortcut data can be retrieved from the cache instead of directly from the external source. This improves performance and can reduce repeated cross-cloud data access.

In this scenario, the Products and Stores shortcuts qualify for cached retrieval, while the Trips shortcut does not. Therefore, only Products and Stores retrieve data from cache.

Question 17: Accessing an Azure SQL Database with Public Access Disabled

You have a Fabric workspace named Workspace1 that contains an Apache Spark job definition named Job1.

You have an Azure SQL database named Source1 that has public internet access disabled.

You need to ensure that Job1 can access the data in Source1. What should you create?

1. An on-premises data gateway
2. A managed private endpoint
3. An integration runtime
4. A data management gateway

Correct Answer: B. A managed private endpoint

Explanation

A managed private endpoint enables secure private connectivity from Fabric to supported Azure resources such as Azure SQL Database. It allows traffic to flow over a private network path instead of public internet access.

Since public internet access is disabled on Source1, a normal public connection will not work. The managed private endpoint is the correct way to allow the Spark job to securely reach the Azure SQL database.

Question 18: Cached Shortcuts from Azure Data Lake Storage and Amazon S3

You have an Azure Data Lake Storage Gen2 account named storage1 and an Amazon S3 bucket named storage2. You have Delta Parquet files such as ProductFile, TripsFile, and StoreFile.

A Fabric workspace named Workspace1 has shortcut caching enabled. Lakehouse1 contains the following shortcuts:

• A shortcut to ProductFile aliased as Products
• A shortcut to StoreFile aliased as Stores
• A shortcut to TripsFile aliased as Trips

The data from which shortcuts will be retrieved from the cache?

1. Trips and Stores only
2. Products and Stores only
3. Stores only
4. Products only
5. Products, Stores, and Trips

Correct Answer: B. Products and Stores only

Explanation

Shortcut caching can improve performance by storing eligible shortcut data locally in Fabric. However, not every shortcut is necessarily retrieved from cache. The eligibility depends on the shortcut source, file characteristics, and caching behavior.

In this case, Products and Stores are retrieved from cache. The Trips shortcut is not retrieved from cache, so the correct answer is Products and Stores only.

Question 19: Orchestrating Notebooks, Pipelines, and Semantic Model Refresh

You have a Fabric workspace named Workspace1 that contains the following items:

• Notebook1
• Notebook2
• Lakehouse1
• Pipeline1
• Model1

For Model1, the Keep your Direct Lake data up to date option is disabled.

You need to configure execution to meet these requirements:

• Notebook1 must execute every weekday at 8:00 AM.
• Notebook2 must execute when a file is saved to an Azure Blob Storage container.
• Model1 must refresh when Notebook1 has executed successfully.

Correct Answer:

• Notebook1: Add Notebook1 to Pipeline1.
• Notebook2: From Real-Time hub, configure the execution of Notebook2.
• Pipeline1: Configure the execution of Pipeline1 by using a schedule.
• Model1: Add Model1 to Pipeline1.

Explanation

To schedule Notebook1 every weekday at 8:00 AM, the notebook should be added to a data pipeline, and the pipeline should be scheduled accordingly.

Notebook2 needs to respond when a file is saved to Azure Blob Storage. This type of event-driven execution can be configured through Real-Time hub.

Since Model1 must refresh after Notebook1 succeeds, the semantic model refresh should be added as a pipeline activity after Notebook1 with a success dependency. Because the Direct Lake automatic update option is disabled, a controlled refresh step is required.

Question 20: Assigning Permissions for Fabric Domains

Your company has a sales department that uses two Fabric workspaces named Workspace1 and Workspace2. The company decides to implement a domain strategy to organize the workspaces.

You need to ensure that a user can perform the following tasks:

• Create a new domain for the sales department.
• Create two subdomains: one for the east region and one for the west region.
• Assign Workspace1 to the east region subdomain.
• Assign Workspace2 to the west region subdomain.

The solution must follow the principle of least privilege. Which role should you assign to the user?

1. Workspace Admin
2. Domain admin
3. Domain contributor
4. Fabric admin

Correct Answer: D. Fabric admin

Explanation

Creating new Fabric domains and subdomains is an administrative task. A Fabric admin has the required permissions to create domains, create subdomains, and manage workspace assignment to those domains.

A workspace admin can manage a specific workspace but cannot create organization-level domains. Domain roles are useful after a domain exists, but the creation of the top-level domain requires higher administrative permissions. Therefore, the Fabric admin role is required.

Summary of DP-700 Practice Questions Part 2

Frequently Asked Questions

What is a Fabric deployment pipeline?

A Fabric deployment pipeline is used to move supported Fabric items between development, test, and production workspaces. It helps manage lifecycle deployment and validation across environments.

What is an eventhouse in Microsoft Fabric?

An eventhouse is a Real-Time Intelligence item in Microsoft Fabric used for storing and analyzing event-based data, commonly queried by using KQL.

Why use a service principal with Azure DevOps and Fabric?

A service principal is used for secure application-based authentication. It is suitable for automation scenarios such as calling Fabric APIs from Azure DevOps pipelines.

What is a managed private endpoint in Fabric?

A managed private endpoint allows Fabric workloads to connect securely to supported Azure resources over a private connection when public access is disabled.

Why is shortcut caching useful in Microsoft Fabric?

Shortcut caching can improve query performance and reduce repeated access to external data sources by caching eligible shortcut data within Fabric.

Final Thoughts

This second set of DP-700 practice questions covered several important Microsoft Fabric exam areas, including deployment pipelines, eventhouse behavior, OneLake availability, secure API authentication, managed private endpoints, shortcut caching, and orchestration.

For the DP-700 exam, always pay attention to phrases such as minimize development effort, principle of least privilege, highest throughput, and built-in functionality. These phrases often guide you toward the correct Fabric feature.