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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 (Q167-Q172):

NEW QUESTION # 167
You have a Fabric workspace named Workspace1 that contains the following items:
A warehouse named Warehouse1
A semantic model named Model1
An interactive report named Report1
You need to allow a user named User1 to access a single table in Warehouse1. The solution must follow the principle of least privilege.
What should you do first?

Answer: B

Explanation:
Requirement
Fabric workspace: Workspace1
Contains: Warehouse1, Model1, Report1
Task: Allow User1 to access a single table in Warehouse1.
Must follow principle of least privilege # grant only the exact permissions required.
Step 1: Evaluate Options
A). Assign object level permissions to User1 for Warehouse1.
In Fabric warehouses, you can grant permissions at the object level (table, schema, or column).
If the requirement is access to only one table, the correct approach is to grant SELECT permissions on that specific table.
This satisfies least privilege.
Correct. #
B). Assign the db_datareader role to User1 for Warehouse1.
db_datareader provides read access to all tables in the database/warehouse.
This violates least privilege.
Not correct.
C). Share Warehouse1 with User1.
Sharing grants access to the whole warehouse.
Too broad, not least privilege.
Not correct.
D). Assign the Viewer role to User1 for Workspace1.
Viewer role allows seeing all items in the workspace (warehouse, model, reports).
This would expose more than the single table.
Not correct.
Step 2: Correct Action
Use object-level permissions:
GRANT SELECT ON dbo.TableName TO [User1];
This ensures User1 can only query that specific table, nothing else.
References
Manage object-level security in Microsoft Fabric warehouses
Principle of least privilege in Fabric


NEW QUESTION # 168
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).
Final Answer:
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 # 169
You have source data in a CSV file that has the following fields:
* SalesTra nsactionl D
* SaleDate
* CustomerCode
* CustomerName
* CustomerAddress
* ProductCode
* ProductName
* Quantity
* UnitPrice
You plan to implement a star schema for the tables in WH1. Thedimension tables in WH1 will implement Type 2 slowly changing dimension (SCD) logic.
You need to design the tables that will be used for sales transaction analysis and load the source data.
Which type of target table should you specify for the CustomerName, CustomerCode, and SaleDate fields?
To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 170
You have a Fabric tenant named Tenant! that contains a lakehouse named Lakehouse1.
You need to add data to Lakehouse1 from a CSV file in an Azure Storage account outside of Fabric. The solution must minimize development effort.
What should you use to add the data?

Answer: A


NEW QUESTION # 171
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 # 172
......

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