This is the free Microsoft DP-700 practice question bank —
60 of 115 total questions, each with a full explanation, free to
read with no signup required. Updated 2026-04-24.
Every answer is verified against official Microsoft documentation —
see our methodology.
Question 1
You have a Microsoft Power Apps app named App1 that has data stored in Microsoft Dataverse.
You need to access the App1 data by using Fabric.
What should you use?
A. a data pipeline
B. mirroring
C. Dataflow Gen2
D. a shortcut
Show Answer
Correct Answer: D
Explanation: Microsoft Fabric provides a native Dataverse shortcut that creates a virtual link from OneLake to Dataverse tables without copying data. This is the recommended and simplest way to access Power Apps (Dataverse) data from Fabric. Data pipelines and Dataflow Gen2 can ingest Dataverse data, but they perform data movement, which is not required when the goal is direct access. Mirroring is not used for Dataverse in this scenario.
Question 1
HOTSPOT
-
You have the development groups shown in the following table.
You have the projects shown in the following table.
You need to recommend which Fabric item to use based on each development group’s skillset. The solution must meet the project requirements and minimize development effort.
What should you recommend for each group? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Show Answer
Correct Answer: Group1: An eventstream
Group2: A Dataflow Gen2
Group3: A notebook
Explanation: Group1 has Azure Stream Analytics/Event Hubs skills and needs to move streaming data → Eventstream.
Group2 uses Power BI and needs low-code transformations → Dataflow Gen2.
Group3 knows R and needs data transformation → Notebook supports code-based transformations.
Question 2
HOTSPOT
-
You have Fabric lakehouse that contains a table named Table1. Table1 stores data in the following format.
You have a notebook that contains the following code segment.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Show Answer
Correct Answer: Line 01: No
Line 02: Yes
Line 03: Yes
Explanation: Line 01 only replaces NULL values using isNull(), not empty strings.
Line 02 splits Email on '.' and getItem(1) returns the segment after the first period, creating column Firstname as defined.
Line 03 uses year(OrderDate) and aliases it as Year, correctly extracting and naming the year column.
Question 2
You have a Fabric workspace that contains a lakehouse named Lakehouse1.
In an external data source, you have data files that are 500 GB each. A new file is added every day.
You need to ingest the data into Lakehouse1 without applying any transformations. The solution must meet the following requirements:
• Trigger the process when a new file is added.
• Provide the highest throughput.
Which type of item should you use to ingest the data?
A. Environment
B. Data pipeline
C. Eventstream
D. KQL queryset
Show Answer
Correct Answer: B
Explanation: A Fabric data pipeline supports event-based triggers when new files arrive and can use the Copy activity to ingest very large files directly into a Lakehouse without transformations, providing the highest throughput. Other options are not designed for bulk file ingestion.
Question 3
DRAG DROP
-
In the Development workspace, you build a new feature named Feature1.
You need to deploy Feature1 to the Test workspace. The solution must ensure that only a pipeline is deployed.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Show Answer
Correct Answer: Select the Test stage.
From Deploy from, select Development.
Select pipeline1.
Select Deploy.
Explanation: You target the Test workspace, choose Development as the deployment source, scope the deployment to only the pipeline item (pipeline1), and then deploy, ensuring no other artifacts are included.
Question 3
You have a Fabric workspace named Workspace1 that contains three notebooks named notebook_01, notebook_02, and notebook_03.
You are building a new notebook in Workspace1 that will contain the following Directed Acyclic Graph (DAG) definition.
You need to modify the DAG definition to meet the following requirements:
• Ensure that notebook_01 and notebook_02 run in parallel.
• Ensure that notebook_02 only runs after the execution of notebook_03 is complete.
How should you modify the DAG definition?
A. Create a second DAG definition. Move notebook_03 and notebook_02 to the new DAG definition.
B. Move the notebook_03 declaration to the top of the DAG definition. Add a concurrency to notebook_02 and notebook_01.
C. Create two stages in the DAG definition. Add notebook_03 to the first stage. Add notebook_01 and notebook_02 to the second stage.
D. Move the declaration of notebook_03 to the top of the DAG definition. Add a new stage that contains notebook_01 and notebook_02.
Show Answer
Correct Answer: C
Explanation: Using stages enforces execution order between groups while allowing parallelism within a stage. Placing notebook_03 in the first stage ensures it completes first. Placing notebook_01 and notebook_02 in the second stage allows them to run in parallel, with notebook_02 starting only after notebook_03 has finished.
Question 4
You have a Fabric workspace that contains a lakehouse named Lakehouse1.
In an external data source, you have data files that are 500 GB each. A new file is added every day.
You need to ingest the data into Lakehouse1 without applying any transformations. The solution must meet the following requirements
• Trigger the process when a new file is added.
• Provide the highest throughput.
Which type of item should you use to ingest the data?
A. Reflex
B. Eventstream
C. Notebook
D. KQL queryset
Show Answer
Correct Answer: C
Explanation: To ingest very large files (500 GB) into a Fabric Lakehouse with the highest possible throughput and without transformations, a Spark-based ingestion is required. A Notebook uses Spark, which is optimized for large-scale, high-throughput file ingestion directly into a Lakehouse. While Eventstream and Reflex support event-based triggers, they are designed for streaming/event data and not for efficiently ingesting very large batch files. A notebook can be triggered via Fabric orchestration (for example, with file-arrival triggers) and provides the necessary performance and control. KQL queryset is only for querying, not ingestion.
Question 5
You have a Fabric workspace named Workspace1 that contains a warehouse named Warehouse1.
You plan to deploy Warehouse 1 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 and provide detailed information about the invalid references.
What should you use?
A. a dbt project
B. a deployment pipeline
C. a Python script
D. a database project
Show Answer
Correct Answer: B
Explanation: Microsoft Fabric deployment pipelines are designed to deploy items like warehouses between workspaces and include built-in validation. During deployment, the pipeline checks for invalid references (such as missing objects or dependencies in the target workspace) and surfaces detailed diagnostic information, all with minimal development effort compared to custom scripts or projects.
Question 6
You have a Fabric F32 capacity that contains a workspace. The workspace contains a warehouse named DW1 that is modelled by using MD5 hash surrogate keys.
DW1 contains a single fact table that has grown from 200 million rows to 500 million rows during the past year.
You have Microsoft Power BI reports that are based on Direct Lake. The reports show year-over-year values.
Users report that the performance of some of the reports has degraded over time and some visuals show errors.
You need to resolve the performance issues. The solution must meet the following requirements:
• Provide the best query performance.
• Minimize operational costs.
Which should you do?
A. Create views.
B. Modify the surrogate keys to use a different data type.
C. Change the MD5 hash to SHA256.
D. Increase the capacity.
E. Disable V-Order on the warehouse.
Show Answer
Correct Answer: D
Explanation: The fact table has grown to 500 million rows, which exceeds the practical and documented limits for optimal Direct Lake performance on an F32 capacity. This results in excessive paging and query degradation, explaining both the performance issues and visual errors. Increasing the Fabric capacity provides more memory and compute, delivering the best query performance. Other options either do not address the Direct Lake capacity constraints or would require significant redesign effort without guaranteeing resolution. While capacity increases cost, it is the only option that directly resolves the root cause at scale.
Question 7
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?
A. SECURITY POLICY
B. TABLE
C. TRIGGER
D. STORED PROCEDURE
Show Answer
Correct Answer: A
Explanation: In a Fabric (SQL) warehouse, row-level security is enforced by creating a SECURITY POLICY, which binds a predicate function to a table and applies row filtering automatically for querying users. Tables store data but do not enforce RLS logic by themselves, triggers do not control query-time row filtering, and stored procedures are not used to implement RLS.
$19
Get all 115 questions with detailed answers and explanations
Instant download HTML + PDF delivered the moment payment clears.
Secure Stripe checkout we never see or store your card details.
7-day refund if files are defective see our refund policy.
