Best Microsoft DP-700 Exam Practice Material Updated on Sep 28, 2026 [Q70-Q84]

September 28, 2026September 28, 2026 examdumpsBest Microsoft DP-700 Exam Practice Material Updated on Sep 28, 2026 [Q70-Q84] 0 Comment

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Best Microsoft DP-700 Exam Practice Material Updated on Sep 28, 2026

New DP-700 Actual Exam Dumps, Microsoft Practice Test

Microsoft DP-700 Exam Syllabus Topics:

Topic	Details
Topic 1	Implement and manage an analytics solution: This section of the exam measures the skills of Microsoft Data Analysts regarding configuring various workspace settings in Microsoft Fabric. It focuses on setting up Microsoft Fabric workspaces, including Spark and domain workspace configurations, as well as implementing lifecycle management and version control. One skill to be measured is creating deployment pipelines for analytics solutions.
Topic 2	Ingest and transform data: This section of the exam measures the skills of Data Engineers that cover designing and implementing data loading patterns. It emphasizes preparing data for loading into dimensional models, handling batch and streaming data ingestion, and transforming data using various methods. A skill to be measured is applying appropriate transformation techniques to ensure data quality.
Topic 3	Monitor and optimize an analytics solution: This section of the exam measures the skills of Data Analysts in monitoring various components of analytics solutions in Microsoft Fabric. It focuses on tracking data ingestion, transformation processes, and semantic model refreshes while configuring alerts for error resolution. One skill to be measured is identifying performance bottlenecks in analytics workflows.

Q70. You have a Fabric workspace that contains an eventhouse and a KQL database named Database1. Database1 has the following:
Policy1 sends data from Table1 to Table2.
The following is a sample of the data in Table2.

Recently, the following actions were performed on Table1:
You plan to load additional records to Table2.
Which two records will load from Table1 to Table2? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

Changes to Table1 Structure:
Impact of Changes:
Record B:
Accepted because it fully matches Table2’s structure and data types.
Record D:
Accepted because it fully matches Table2’s structure and data types.

Q71. You have a Fabric .
In Warehouse1, you create a table named DimCustomer by running the following statement.

You need to set the Customerkey column as a primary key of the DimCustomer table.
Which three code segments should you run in sequence? To answer, move the appropriate code segments from the list of code segments to the answer area and arrange them in the correct order.

Explanation:

Q72. HOTSPOT
You have a Fabric workspace.
You are debugging a statement and discover the following issues:
Sometimes, the statement fails to return all the expected rows.
The PurchaseDate output column is NOT in the expected format of mmm dd, yy.
You need to resolve the issues. The solution must ensure that the data types of the results are retained. The results can contain blank cells.
How should you complete the statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Explanation:

Q73. Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a KQL database that contains two tables named Stream and Reference. Stream contains streaming data in the following format.

Reference contains reference data in the following format.

Both tables contain millions of rows.
You have the following KQL queryset.

You need to reduce how long it takes to run the KQL queryset.
Solution: You change the join type to kind=outer.
Does this meet the goal?

Yes

An outer join will include unmatched rows from both tables, increasing the dataset size and processing time.
It does not improve query performance.

Q74. You have three users named User1, User2, and User3.
You have the Fabric workspaces shown in the following table.

You have a security group named Group1 that contains User1 and User3.
The Fabric admin creates the domains shown in the following table.

User1 creates a new workspace named Workspace3.
You add Group1 to the default domain of Domain1.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Q75. Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a Fabric eventstream that loads data into a table named Bike_Location in a KQL database. The table contains the following columns:
BikepointID
Street
Neighbourhood
No_Bikes
No_Empty_Docks
Timestamp
You need to apply transformation and filter logic to prepare the data for consumption. The solution must return data for a neighbourhood named Sands End when No_Bikes is at least 15. The results must be ordered by No_Bikes in ascending order.
Solution: You use the following code segment:

Does this meet the goal?

Yes

This code does not meet the goal because it uses order by, which is not valid in KQL. The correct term in KQL is sort by.
Correct code should look like:

Topic 1, Litware, IncCase Study
This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
Overview
Litware, Inc. is a publishing company that has an online bookstore and several retail bookstores worldwide.
Litware also manages an online advertising business for the authors it represents.
Existing Environment. Fabric Environment
Litware has a Fabric workspace named Workspace1. High concurrency is enabled for Workspace1.
The company has a data engineering team that uses Python for data processing.
Existing Environment. Data Processing
The retail bookstores send sales data at the end of each business day, while the online bookstore constantly provides logs and sales data to a central enterprise resource planning (ERP) system.
Litware implements a medallion architecture by using the following three layers: bronze, silver, and gold. The sales data is ingested from the ERP system as Parquet files that land in the Files folder in a lakehouse.
Notebooks are used to transform the files in a Delta table for the bronze and silver layers. The gold layer is in a warehouse that has V-Order disabled.
Litware has image files of book covers in Azure Blob Storage. The files are loaded into the Files folder.
Existing Environment. Sales Data
Month-end sales data is processed on the first calendar day of each month. Data that is older than one month never changes.
In the source system, the sales data refreshes every six hours starting at midnight each day.
The sales data is captured in a Dataflow Gen1 dataflow. When the dataflow runs, new and historical data is captured. The dataflow captures the following fields of the source:
Sales Date
Author
Price
Units
SKU
A table named AuthorSales stores the sales data that relates to each author. The table contains a column named AuthorEmail. Authors authenticate to a guest Fabric tenant by using their email address.
Existing Environment. Security Groups
Litware has the following security groups:
Sales
Fabric Admins
Streaming Admins
Existing Environment. Performance Issues
Business users perform ad-hoc queries against the warehouse. The business users indicate that reports against the warehouse sometimes run for two hours and fail to load as expected. Upon further investigation, the data engineering team receives the following error message when the reports fail to load: “The SQL query failed while running.” The data engineering team wants to debug the issue and find queries that cause more than one failure.
When the authors have new book releases, there is often an increase in sales activity. This increase slows the data ingestion process.
The company’s sales team reports that during the last month, the sales data has NOT been up-to-date when they arrive at work in the morning.
Requirements. Planned Changes
Litware recently signed a contract to receive book reviews. The provider of the reviews exposes the data in Amazon Simple Storage Service (Amazon S3) buckets.
Litware plans to manage Search Engine Optimization (SEO) for the authors. The SEO data will be streamed from a REST API.
Requirements. Version Control
Litware plans to implement a version control solution in Fabric that will use GitHub integration and follow the principle of least privilege.
Requirements. Governance Requirements
To control data platform costs, the data platform must use only Fabric services and items. Additional Azure resources must NOT be provisioned.
Requirements. Data Requirements
Litware identifies the following data requirements:
Process the SEO data in near-real-time (NRT).
Make the book reviews available in the lakehouse without making a copy of the data.
When a new book cover image arrives in the Files folder, process the image as soon as possible.

Q76. You have a Fabric workspace named Workspace1. Your company acquires GitHub licenses.
You need to configure source control for Workpace1 to use GitHub. The solution must follow the principle of least privilege. Which permissions do you require to ensure that you can commit code to GitHub?

Actions (Read and write) and Contents (Read and write)

Actions (Read and write) only

Contents (Read and write) only

Contents (Read) and Commit statuses (Read and write)

Q77. You have an Azure key vault named KeyVaultl that contains secrets.
You have a Fabric workspace named Workspace!. Workspace! contains a notebook named Notebookl that performs the following tasks:
* Loads stage data to the target tables in a lakehouse
* Triggers the refresh of a semantic model
You plan to add functionality to Notebookl that will use the Fabric API to monitor the semantic model refreshes. You need to retrieve the registered application ID and secret from KeyVaultl to generate the authentication token. Solution: You use the following code segment:
Use notebookutils. credentials.getSecret and specify key vault URL and the name of a linked service.
Does this meet the goal?

Yes

Q78. You need to schedule the population of the medallion layers to meet the technical requirements.
What should you do?

Schedule a data pipeline that calls other data pipelines.

Schedule a notebook.

Schedule an Apache Spark job.

Schedule multiple data pipelines.

The technical requirements specify that:
Why Use a Data Pipeline That Calls Other Data Pipelines?
– Sequential execution of child pipelines.
– Error handling to send email notifications upon failures.
– Parallel execution of tasks where possible (e.g., simultaneous imports into the bronze layer).

Q79. You need to schedule the population of the medallion layers to meet the technical requirements.
What should you do?

Schedule a data pipeline that calls other data pipelines.

Schedule a notebook.

Schedule an Apache Spark job.

Schedule multiple data pipelines.

The technical requirements specify that:
Medallion layers must be fully populated sequentially (bronze # silver # gold). Each layer must be populated before the next.
If any step fails, the process must notify the data engineers.
Data imports should run simultaneously when possible.
Why Use a Data Pipeline That Calls Other Data Pipelines?
A data pipeline provides a modular and reusable approach to orchestrating the sequential population of medallion layers.
By calling other pipelines, each pipeline can focus on populating a specific layer (bronze, silver, or gold), simplifying development and maintenance.
A parent pipeline can handle:
– Sequential execution of child pipelines.
– Error handling to send email notifications upon failures.
– Parallel execution of tasks where possible (e.g., simultaneous imports into the bronze layer).

Q80. 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?

GitHub Actions

a deployment pipeline

an Azure DevOps pipeline

A deployment pipeline in Fabric is designed to automate the process of deploying assets (such as reports, datasets, eventhouses, and other objects) between environments like Dev, Test, and Prod. Since you need to deploy an eventhouse as part of the deployment process, a deployment pipeline is the appropriate tool to move this asset through the different stages of your environment.

Q81. HOTSPOT
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.

Explanation:

Q82. You are building a data orchestration pattern by using a Fabric data pipeline named Dynamic Data Copy as shown in the exhibit. (Click the Exhibit tab.)

Dynamic Data Copy does NOT use parametrization.
You need to configure the ForEach activity to receive the list of tables to be copied.
How should you complete the pipeline expression? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Explanation:

Q83. You are developing a data pipeline named Pipeline1.
You need to add a Copy data activity that will copy data from a Snowflake data source to a Fabric warehouse. Which option from the Settings tab of the Copy data activity must you configure?

Enable logging

Fault tolerance

Enable staging

Degree of copy parallelism

Q84. You have three users named User1, User2, and User3.
You have the Fabric workspaces shown in the following table.

You have a security group named Group1 that contains User1 and User3.
The Fabric admin creates the domains shown in the following table.

User1 creates a new workspace named Workspace3.
You add Group1 to the default domain of Domain1.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.