USE Microsoft DP-600 QUESTIONS TO SPEED UP EXAM PREPARATION [2026]

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Microsoft DP-600 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Implement and manage semantic models: This section of the exam measures the skills of architects and focuses on designing and optimizing semantic models to support enterprise-scale analytics. It evaluates understanding of storage modes and implementing star schemas and complex relationships, such as bridge tables and many-to-many joins. Architects must write DAX-based calculations using variables, iterators, and filtering techniques. The use of calculation groups, dynamic format strings, and field parameters is included. The section also includes configuring large semantic models and designing composite models. For optimization, candidates are expected to improve report visual and DAX performance, configure Direct Lake behaviors, and implement incremental refresh strategies effectively.
Topic 2
  • Maintain a data analytics solution: This section of the exam measures the skills of administrators and covers tasks related to enforcing security and managing the Power BI environment. It involves setting up access controls at both workspace and item levels, ensuring appropriate permissions for users and groups. Row-level, column-level, object-level, and file-level access controls are also included, alongside the application of sensitivity labels to classify data securely. This section also tests the ability to endorse Power BI items for organizational use and oversee the complete development lifecycle of analytics assets by configuring version control, managing Power BI Desktop projects, setting up deployment pipelines, assessing downstream impacts from various data assets, and handling semantic model deployments using XMLA endpoint. Reusable asset management is also a part of this domain.
Topic 3
  • Prepare data: This section of the exam measures the skills of engineers and covers essential data preparation tasks. It includes establishing data connections and discovering sources through tools like the OneLake data hub and the real-time hub. Candidates must demonstrate knowledge of selecting the appropriate storage type—lakehouse, warehouse, or eventhouse—depending on the use case. It also includes implementing OneLake integrations with Eventhouse and semantic models. The transformation part involves creating views, stored procedures, and functions, as well as enriching, merging, denormalizing, and aggregating data. Engineers are also expected to handle data quality issues like duplicates, missing values, and nulls, along with converting data types and filtering. Furthermore, querying and analyzing data using tools like SQL, KQL, and the Visual Query Editor is tested in this domain.

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Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q67-Q72):

NEW QUESTION # 67
You have a Fabric tenant that contains a semantic model. The model contains data about retail stores.
You need to write a DAX query that will be executed by using the XMLA endpoint. The query must return the total amount of sales from the same period last year.
How should you complete the DAX expression? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 68
You need to refresh the Orders table of the Online Sales department. The solution must meet the semantic model requirements. What should you include in the solution?

Answer: B

Explanation:
Requirement: "The number of rows added to the Orders table during refreshes must be minimized." The Orders table has a sequential OrderID.
To minimize refresh size, you must only import new rows, not the entire table.
This requires retrieving the maximum OrderID currently loaded, then only loading rows with a greater OrderID.
So, the correct solution is to use a pipeline (ADF) with a dataflow to retrieve the maximum OrderID.
an Azure Data Factory pipeline that executes a dataflow to retrieve the maximum value of the OrderID column in the destination lakehouse


NEW QUESTION # 69
You have the following T-SQI statement.

Answer:

Explanation:

Explanation:

The statement uses SUM(CASE WHEN RefundStatus = 'Refunded' THEN SalesAmount ELSE 0 END) AS TotalRevenue, which calculates TotalRevenue by summing SalesAmount only when RefundStatus is
'Refunded', and 0 otherwise. This means Region values are returned regardless of RefundStatus, but the TotalRevenue reflects refunded items.
The WHERE (TransactionDate) - YEAR(GETDATE()) condition is incomplete and lacks proper comparison (e.g., no equality or range check), so it does not filter for the current year.
The TotalRevenue calculation does not aggregate all SalesAmount values with RefundStatus of 'Refunded'; it sums SalesAmount only for refunded items within the grouped data, with 0 for non-refunded items.


NEW QUESTION # 70
You have a semantic model named Model1 that contains data that relates to customers and their bank account balances.
Model1 has the following tables and columns.

A custome r can have one or more accounts. Each account can be associated to multiple customers.
You need to ensure that users can query Model1 to identify the total transaction amounts by customer.
What should you add to Model1?

Answer: C

Explanation:
Scenario:
Tables:
DimAccount (accounts)
FactTransaction (transactions)
DimCustomer (customers)
Business rule:
A customer can have multiple accounts .
An account can be linked to multiple customers .
Many-to-many relationship.
Requirement: Calculate total transaction amounts by customer .
Analysis:
Direct many-to-many between FactTransaction and DimCustomer would not properly resolve aggregation.
Adding CustomerKey directly in FactTransaction is not possible because transactions link to accounts, not customers directly.
Correct approach: Create a bridge table (CustomerAccount) that maps Customer # Account .
Then link FactTransaction # DimAccount # Bridge # DimCustomer .
C). A bridge table with relationships to DimCustomer and DimA ccount


NEW QUESTION # 71
You have a Fabric tenant that contains a semantic model. The model contains data about retail stores.
You need to write a DAX query that will be executed by using the XMLA endpoint The query must return a table of stores that have opened since December 1,2023.
How should you complete the DAX expression? To answer, drag the appropriate values to the correct targets.
Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
The correct order for the DAX expression would be:
* DEFINE VAR _SalesSince = DATE ( 2023, 12, 01 )
* EVALUATE
* FILTER (
* SUMMARIZE ( Store, Store[Name], Store[OpenDate] ),
* Store[OpenDate] >= _SalesSince )
In this DAX query, you're defining a variable _SalesSince to hold the date from which you want to filter the stores. EVALUATE starts the definition of the query. The FILTER function is used to return a table that filters another table or expression. SUMMARIZE creates a summary table for the stores, including the Store
[Name] and Store[OpenDate] columns, and the filter expression Store[OpenDate] >= _SalesSince ensures only stores opened on or after December 1, 2023, are included in the results.
References =
* DAX FILTER Function
* DAX SUMMARIZE Function


NEW QUESTION # 72
......

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