Cisco
CompTIA
ISC
EC-Council
EXIN
Fortinet
ITIL
Juniper
Microsoft
VMware
Avaya
SAP
Google
NVIDIA
Salesforce
Amazon
Palo Alto Networks
ISC2
Splunk
ServiceNow
All Vendors
  2. Home
  3. Exams
  4. Microsoft
  5. DP-700

Microsoft DP-700 Exam Questions
Implementing Data Engineering Solutions Using Microsoft Fabric (Page 4 )

Updated On: 25-Apr-2026
Page 3 of 16
PDF with 125 Questions

HOTSPOT (Drag and Drop is not supported)
You have a Fabric workspace that contains a warehouse named DW1. DW1 contains the following tables and columns.

You need to create an output that presents the summarized values of all the order quantities by year and product. The results must include a summary of the order quantities at the year level for all the products.
How should you complete the code? To answer, select the appropriate options in the answer area.
Note: Each correct selection is worth one point.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Summarize by year and product: The query needs to group data by both year and product name.
Include a summary of order quantities at the year level: This is achieved using grouping mechanisms like ROLLUP or CUBE.
SELECT YEAR(SO.ModifiedDate)
Since we need to summarize the data by year, extracting the year from the ModifiedDate column using YEAR (SO.ModifiedDate) is the correct choice. Other options like CAST or CONVERT do not specifically extract the year.
ROLLUP(YEAR(SO.ModifiedDate), P.Name)
The ROLLUP function creates subtotals for each grouping combination. In this case:
It will group by YEAR(SO.ModifiedDate) and P.Name (product name).
It will also include a summary for all products for each year, which meets the requirement of summarizing order quantities at the year level for all products.



You have a Fabric workspace that contains a lakehouse named Lakehouse1. Data is ingested into Lakehouse1 as one flat table. The table contains the following columns.


You plan to load the data into a dimensional model and implement a star schema. From the original flat table, you create two tables named FactSales and DimProduct. You will track changes in DimProduct.
You need to prepare the data.
Which three columns should you include in the DimProduct table? Each correct answer presents part of the solution.
Note: Each correct selection is worth one point.

  1. Date
  2. ProductName
  3. ProductColor
  4. TransactionID
  5. SalesAmount
  6. ProductID

Answer(s): B,C,F

Explanation:

In a star schema, the DimProduct table serves as a dimension table that contains descriptive attributes about products. It will provide context for the FactSales table, which contains transactional data. The following columns should be included in the DimProduct table:
1. ProductName: The ProductName is an important descriptive attribute of the product, which is needed for analysis and reporting in a dimensional model.
2. ProductColor: ProductColor is another descriptive attribute of the product. In a star schema, it makes sense to include attributes like color in the dimension table to help categorize products in the analysis.
3. ProductID: ProductID is the primary key for the DimProduct table, which will be used to join the FactSales table to the product dimension. It's essential for uniquely identifying each product in the model.



You have a Fabric workspace named Workspace1 that contains a notebook named Notebook1.
In Workspace1, you create a new notebook named Notebook2.
You need to ensure that you can attach Notebook2 to the same Apache Spark session as Notebook1.
What should you do?

  1. Enable high concurrency for notebooks.
  2. Enable dynamic allocation for the Spark pool.
  3. Change the runtime version.
  4. Increase the number of executors.

Answer(s): A

Explanation:

To ensure that Notebook2 can attach to the same Apache Spark session as Notebook1, you need to enable high concurrency for notebooks. High concurrency allows multiple notebooks to share a Spark session, enabling them to run within the same Spark context and thus share resources like cached data, session state, and compute capabilities. This is particularly useful when you need notebooks to run in sequence or together while leveraging shared resources.



You have a Fabric workspace named Workspace1 that contains a lakehouse named Lakehouse1. Lakehouse1 contains the following tables:
Orders
Customer
Employee
The Employee table contains Personally Identifiable Information (PII).
A data engineer is building a workflow that requires writing data to the Customer table, however, the user does NOT have the elevated permissions required to view the contents of the Employee table.
You need to ensure that the data engineer can write data to the Customer table without reading data from the Employee table.
Which three actions should you perform? Each correct answer presents part of the solution.
Note: Each correct selection is worth one point.

  1. Share Lakehouse1 with the data engineer.
  2. Assign the data engineer the Contributor role for Workspace2.
  3. Assign the data engineer the Viewer role for Workspace2.
  4. Assign the data engineer the Contributor role for Workspace1.
  5. Migrate the Employee table from Lakehouse1 to Lakehouse2.
  6. Create a new workspace named Workspace2 that contains a new lakehouse named Lakehouse2.
  7. Assign the data engineer the Viewer role for Workspace1.

Answer(s): D,E,F



You have a Fabric warehouse named DW1. DW1 contains a table that stores sales data and is used by multiple sales representatives.
You plan to implement row-level security (RLS).
You need to ensure that the sales representatives can see only their respective data.
Which warehouse object do you require to implement RLS?

  1. STORED PROCEDURE
  2. CONSTRAINT
  3. SCHEMA
  4. FUNCTION

Answer(s): D

Explanation:

To implement Row-Level Security (RLS) in a Fabric warehouse, you need to use a function that defines the security logic for filtering the rows of data based on the user's identity or role. This function can be used in conjunction with a security policy to control access to specific rows in a table.
In the case of sales representatives, the function would define the filtering criteria (e.g., based on a column such as SalesRepID or SalesRepName), ensuring that each representative can only see their respective data.



HOTSPOT (Drag and Drop is not supported)
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 that each has 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 the items from Workspace1_DEV to Workspace1_TEST.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
Note: Each correct selection is worth one point.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Data from the semantic models will be deployed to the target stage ­ No In a deployment pipeline, data from semantic models (such as cached data) is not typically deployed along with the models themselves.
While the semantic models themselves (including structure and definitions) will be deployed, the actual data (e.g., the results of the model refreshes) will not be automatically transferred. You would need to handle data refreshes separately after the semantic models are deployed.
The Dataflow Gen1 dataflows will be deployed to the target stage ­ Yes Dataflows, including Dataflow Gen1 dataflows, are part of the deployment pipeline and will be deployed to the target stage. These dataflows are part of the solution being deployed, and the pipeline ensures their migration to the target workspace (Workspace1_TEST).
The scheduled refresh policies will be deployed to the target stage ­ No While the scheduled refresh policies for semantic models are part of the configuration, they are not automatically deployed through the pipeline. Deployment pipelines typically move content, such as reports, notebooks, and dataflows, but scheduled refresh settings are not automatically transferred with the deployment. You would need to manually configure the refresh policies in the new workspace (Workspace1_TEST) after the deployment.



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

Answer(s): C

Explanation:

Correct:
* an Azure DevOps pipeline
Incorrect:
* a deployment pipeline
* an eventstream
* GitHub Actions



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

Answer(s): B

Explanation:

A deployment pipeline in Fabric allows you to deploy assets like warehouses, datasets, and reports between different workspaces (such as from Workspace1 to Workspace2). One of the key features of a deployment pipeline is the ability to check for invalid references before deployment. This can help identify issues with assets, such as broken links or dependencies, ensuring the deployment is successful without introducing errors. This is the most efficient way to verify references and manage the deployment with minimal development effort.



Viewing page 4 of 16
Viewing questions 25 - 32 out of 125 questions
Share your experience with other


DP-700 Exam Discussions & Posts

What the DP-700 Exam Tests and How to Pass It

The DP-700: Implementing Data Engineering Solutions Using Microsoft Fabric certification is designed for data engineers who are responsible for designing, implementing, and managing data engineering solutions within the Microsoft Fabric ecosystem. Professionals who pursue this Microsoft certification typically work in roles that require them to integrate, transform, and consolidate data from various sources into a unified analytics platform. Employers look for this credential because it validates a candidate's ability to handle the end-to-end lifecycle of data engineering tasks, ensuring that data is reliable, secure, and ready for downstream analytics or machine learning applications. By passing this exam, candidates demonstrate that they possess the technical proficiency required to maintain high-performance data pipelines and optimize storage solutions in a cloud-based environment. This certification is a key benchmark for organizations that rely on Microsoft Fabric to drive their data-driven decision-making processes.

What the DP-700 Exam Covers

The exam evaluates your ability to implement and manage an analytics solution, which involves configuring the environment and ensuring that data governance and security standards are met throughout the lifecycle. Candidates must demonstrate proficiency in how to ingest and transform data, a core competency that requires understanding various data integration patterns, pipeline orchestration, and the application of transformations to raw data to make it usable for business intelligence. Furthermore, the exam tests your skills in how to monitor and optimize an analytics solution, ensuring that data engineering workloads run efficiently and cost-effectively within the Microsoft Fabric platform. Our practice questions are structured to mirror these functional areas, allowing you to test your knowledge across the entire spectrum of data engineering tasks you will encounter on the job. By engaging with these practice questions, you can identify specific areas where your technical understanding may need reinforcement before sitting for the actual certification exam.

The most technically demanding aspect of the DP-700 exam often involves the intricacies of data transformation and pipeline optimization, as these tasks require a deep understanding of how data flows through the Fabric architecture. Candidates are frequently challenged by scenarios that require them to choose the most efficient transformation method or troubleshoot performance bottlenecks in complex data pipelines. Success in this area requires more than just theoretical knowledge; it demands an applied understanding of how different Fabric components interact under load. You must be prepared to analyze architectural requirements and apply the correct engineering principles to ensure data integrity and system performance, which is why consistent practice with scenario-based questions is essential for thorough exam preparation.

Are These Real DP-700 Exam Questions?

The practice questions available on our platform are sourced and verified by the community, consisting of IT professionals and recent test-takers who have sat for the actual Microsoft certification exam. While we do not provide leaked or confidential content, our questions reflect what appears on the real exam because they are sourced from the community, ensuring that the concepts, question styles, and technical scenarios align with the current exam objectives. If you've been searching for DP-700 exam dumps or braindump files, our community-verified practice questions offer something more valuable, each question is verified and explained by IT professionals who recently passed the exam. This approach ensures that you are studying relevant material that helps you understand the underlying technology rather than simply memorizing patterns that may not appear on the test.

Community verification works through a collaborative process where users actively discuss answer choices, flag potentially incorrect information, and share context from their recent exam experiences. When a question is flagged, it is reviewed by other members of the community to ensure accuracy and clarity, creating a self-correcting system that improves the quality of the study material over time. This peer-review mechanism is what makes our practice questions a reliable resource for your exam prep, as it provides multiple perspectives on how to approach complex data engineering problems. By participating in these discussions, you gain insights into the reasoning behind correct answers, which is far more effective for long-term retention than relying on static, unverified sources.

How to Prepare for the DP-700 Exam

Effective exam preparation for the DP-700 requires a combination of hands-on experience and a solid grasp of the official Microsoft documentation. You should prioritize building a study schedule that allows you to experiment with Microsoft Fabric in a sandbox or development environment, as practical application is the best way to internalize the concepts tested on the exam. Every practice question includes a free AI Tutor explanation that breaks down the reasoning behind the correct answer, so you understand the concept, not just the answer. This AI Tutor serves as an on-demand resource to clarify complex topics, helping you bridge the gap between reading documentation and applying that knowledge to solve real-world data engineering challenges.

A common mistake candidates make is relying solely on rote memorization of facts, which often leads to failure when they encounter scenario-based questions that require critical thinking. The DP-700 exam is designed to test your ability to apply knowledge in specific contexts, meaning you must understand the "why" and "how" behind each data engineering solution, not just the definitions. To avoid this, focus on understanding the architectural trade-offs involved in different data ingestion and transformation strategies. Additionally, many candidates struggle with time management during the certification exam; practicing with timed sets of questions can help you develop the pace necessary to complete the exam without rushing through complex scenarios.

What to Expect on Exam Day

On the day of your exam, you should expect a format that includes a variety of question types, such as multiple-choice, scenario-based questions, and potentially drag-and-drop or ordering tasks that test your procedural knowledge. Microsoft certification exams are typically administered via a secure testing environment, either at a physical Pearson VUE testing center or through an online proctored session. You will be given a set amount of time to complete the exam, and it is important to read each scenario carefully, as the details provided in the prompt are crucial for selecting the correct answer. The exam is designed to be rigorous, ensuring that those who pass have a genuine, verified level of competence in implementing data engineering solutions using Microsoft Fabric.

Who Should Use These DP-700 Practice Questions

These practice questions are intended for data engineers, data architects, and IT professionals who are looking to validate their skills in the Microsoft Fabric ecosystem. Ideally, candidates should have some experience working with data integration, transformation, and analytics solutions before attempting this certification exam. Whether you are looking to advance your career or simply formalize your knowledge, these resources are designed to support your exam preparation journey by providing a structured way to test your readiness. Passing this certification exam is a significant milestone that demonstrates your ability to manage complex data engineering workloads, making you a more competitive candidate in the job market.

To get the most out of these practice questions, do not simply read the answer and move on; instead, engage deeply with the AI Tutor explanation and review the community discussions for each item. If you find yourself consistently getting questions wrong in a specific topic area, flag those questions and revisit them after reviewing the relevant official documentation. This iterative process of testing, reviewing, and re-testing is the most reliable way to build the confidence needed for the actual exam. Browse the questions above and use the community discussions and AI Tutor to build real exam confidence.

Updated on: 27 April, 2026

AI Tutor AI Tutor 👋 I’m here to help!