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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
  • 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.
Topic 3
  • 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.

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Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q90-Q95):

NEW QUESTION # 90
Hotspot Question
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:


NEW QUESTION # 91
You have a Fabric tenant that contains a workspace named Workspace1. Workspace1 contains a lakehouse named Lakehouse1 and a warehouse named Warehouse1.
You need to create a new table in Warehouse1 named POSCustomers by querying the customer table in Lakehouse1.
How should you complete the T-SQL statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

Step 1 - Creating the new table from a query
To create a table in a SQL warehouse using a query, the correct syntax is:
CREATE TABLE <table_name> AS SELECT ...
So we must select:
CREATE TABLE dbo.POSCustomers AS SELECT
Step 2 - Selecting the source table
Since the data source is the Lakehouse1 table Customer, the fully qualified name is:
lakehouse1.dbo.Customer
Final Answer:
CREATE TABLE dbo.POSCustomers AS SELECT
postalcode,
category
FROM lakehouse1.dbo.Customer;
References:
CREATE TABLE AS SELECT (CTAS) in Fabric Warehouse
Fabric Lakehouse and Warehouse interoperability


NEW QUESTION # 92
You need to recommend a solution to group the Research division workspaces.
What should you include in the recommendation? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

Comprehensive Detailed Explanation
The requirement is to logically group the Research division workspaces and support filtering in the OneLake data hub.
Why Domain?
Microsoft Fabric allows you to assign workspace domains (e.g., Finance, HR, Research).
This provides a logical grouping of workspaces within the organization.
Domains are the only supported way to enable filtering in OneLake data hub by department.
Capacity or tenant grouping would not allow filtering by department in OneLake.
Why OneLake data hub?
The OneLake data hub is the centralized interface to browse and discover data assets across the organization.
With workspace domains configured, users can filter directly in the OneLake data hub by domain (e.g.,
"Research").
The Fabric Admin portal and Entra admin center are used for administration, not for workspace filtering in data discovery.
Correct Selection for the Hotspot
Grouping method: Domain
Tool: OneLake data hub
References
Workspace domains in Microsoft Fabric
Discover and filter data in OneLake data hub
Final Answer:
Grouping method = Domain
Tool = OneLake data hub


NEW QUESTION # 93
You to need assign permissions for the data store in the AnalyticsPOC workspace. The solution must meet the security requirements.
Which additional permissions should you assign when you share the data store? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
* Data Engineers: Read All SQL analytics endpoint data
* Data Analysts: Read All Apache Spark
* Data Scientists: Read All SQL analytics endpoint data
The permissions for the data store in the AnalyticsPOC workspace should align with the principle of least privilege:
* Data Engineers need read and write access but not to datasets or reports.
* Data Analysts require read access specifically to the dimensional model objects and the ability to create Power BI reports.
* Data Scientists need read access via Spark notebooks. These settings ensure each role has the necessary permissions to fulfill their responsibilities without exceeding their required access level.


NEW QUESTION # 94
You have Fabric tenant that contains a semantic model named Mode1. Model! contains the following tables.

You are designing a Microsoft Power B1 report named Report! that will deliver near-real-time (NRT) shipping data. Report1 will contain data about many shipped packages.
You need to ensure that each table is in the appropriate storage mode to support Report1. The solution must support near-realtime data delivery while maintaining high query performance.
Which storage mode should you select for each table? To answer, drag the appropriate storage modes to the correct tables. Each mode 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:


NEW QUESTION # 95
......

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