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You need to recommend a solution for handling old files. The solution must meet the technical requirements. What should you include in the recommendation?
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?
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.
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?
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.
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?
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:
You have a Fabric lakehouse that contains the resources shown in the following table.
You need to use a notebook to query for customers in the United States and load the filtered data into USCustomers. The solution must minimize the number of scripts used.
Which statement should you use?
To minimize the number of scripts while querying customers from the United States and loading filtered data into USCustomers, you should use a single SQL statement combining SELECT with a WHERE clause filter and INSERT INTO. This single statement accomplishes both the filtering and loading in one operation: INSERT INTO USCustomers SELECT * FROM Customers WHERE Country = 'United States'. This minimizes script complexity and execution overhead.
149 questions covering all exam domains, starting from $20
Exam domains verified against: Official Microsoft DP-700 exam guide, last checked September 2026.
Configure workspace settings and lifecycle management to establish proper governance foundations. Implement security controls and orchestrate processes to ensure data flows safely through your Fabric environment.
Design loading patterns and build batch pipelines to move data reliably at scale. Work with streaming sources and transformation logic to process continuous data flows using SQL, PySpark, or KQL.
Sample question from this domain above: Q2
Track Fabric item performance and identify bottlenecks to maintain solution health. Resolve runtime errors and tune queries and resource allocation to keep the platform running efficiently.
Common questions about the exam itself
