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Microsoft DP-600 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 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 (Q17-Q22):

NEW QUESTION # 17
Which workspace rote assignments should you recommend for ResearchReviewersGroupl and ResearchReviewersGroupZ? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 18
What should you recommend using to ingest the customer data into the data store in the AnatyticsPOC workspace?

Answer: C


NEW QUESTION # 19
You have a Fabric tenant that contains a warehouse named WH1. You run the following T-SQL query against WH1.

For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

We are analyzing the query:
SELECT e.[WWI Employee ID],
e.Employee,
e.[Preferred Name],
gdr.[WWI Employee ID] AS [Direct Report ID],
gdr.Employee AS [Direct Report]
FROM Dimension.Employee AS e
OUTER APPLY Dimension.GetDirectReports(e.[Employee Key]) AS gdr;
Key concepts:
APPLY operator : Used to join a table with a table-valued function .
OUTER APPLY ensures all rows from the left (Employee) are returned, even if the function returns no rows (similar to LEFT JOIN).
Table-valued function (TVF) : Returns a set of rows (unlike scalar functions, which return a single value).
The function executes once per row from the left table, not once for the whole query.
Evaluating each statement:
" Dimension.GetDirectReports is a scalar T-SQL function. "
No # It must be a table-valued function , because OUTER APPLY requires a table expression.
" The Dimension.GetDirectReports function will run only once when the query runs. " No # With APPLY , the function runs for each row of Dimension.Employee .
" The output rows will include at least one row for each row in the Dimension.Employee table. " Yes # Because of OUTER APPLY , every employee row is included, even if there are no direct reports (in that case, the columns from gdr will be NULL).
Scalar function # No
Runs once per query # No
At least one row per Employee # Yes
References:
APPLY operator in T-SQL
Table-valued functions


NEW QUESTION # 20
You have a Fabric tenant that contains a data pipeline.
You need to ensure that the pipeline runs every four hours on Mondays and Fridays.
To what should you set Repeat for the schedule?

Answer: D

Explanation:
You should set Repeat for the schedule to Weekly (C). This allows you to specify the pipeline to run on specific days of the week, in this case, every four hours on Mondays and Fridays. Reference = Scheduling options for data pipelines are available in the Azure Data Factory documentation, which includes details on configuring recurring triggers.


NEW QUESTION # 21
You have a Fabric tenant that contains a semantic model named Model1.
Modell contains a table named TemperatureUnit. TempetatuieUnit contains a column named Unit. Unit contains manually added options for Celsius and Fahrenheit.
Model1 contains the following measures:

You need to add a dynamic format string to the [TemperatureDisplay] measure to enable users to switch display values between metric (Celsius) and imperial (Fahrenheit).
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 # 22
......

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