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| Topic | Details |
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| Topic 1 | - 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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| 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.
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| Topic 3 | - 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.
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Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q167-Q172):
NEW QUESTION # 167
You have a Fabric tenant that contains a workspace named Workspace1.
You plan to deploy a semantic model named Model1 by using the XMLA endpoint.
You need to optimize the deployment of Model1. The solution must minimize how long it takes to deploy Model1.
What should you do in Workspace1?
- A. Select Users can edit data models in the Power BI service.
- B. Set Enable Cache for Shortcuts to On.
- C. Select Large semantic model storage format.
- D. Select Small semantic model storage format.
Answer: D
NEW QUESTION # 168
You have a Microsoft Fabric tenant that contains a dataflow.
You are exploring a new semantic model.
From Power Query, you need to view column information as shown in the following exhibit.

Which three Data view options should you select? Each correct answer presents part of the solution. NOTE:
Each correct answer is worth one point.
- A. Show column value distribution
- B. Enable details pane
- C. Show column profile in details pane
- D. Enable column profile
- E. Show column quality details
Answer: B,D,E
Explanation:
To view column information like the one shown in the exhibit in Power Query, you need to select the options that enable profiling and display quality and distribution details. These are: A. Enable column profile - This option turns on profiling for each column, showing statistics such as distinct and unique values. B. Show column quality details - It displays the column quality bar on top of each column showing the percentage of valid, error, and empty values. E. Show column value distribution - It enables the histogram display of value distribution for each column, which visualizes how often each value occurs.
References: These features and their descriptions are typically found in the Power Query documentation, under the section for data profiling and quality features.
NEW QUESTION # 169
You have a Fabric tenant that contains a lakehouse named LH1.
You need to deploy a new semantic model. The solution must meet the following requirements:
* Support complex calculated columns that include aggregate functions, calculated tables, and Multidimensional Expressions (MDX) user hierarchies.
* Minimize page rendering times.
How should you configure the model? 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 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 # 171
You have a Fabric workspace named Workspace1 and an Azure Data Lake Storage Gen2 account named storage"!. Workspace1 contains a lakehouse named Lakehouse1.
You need to create a shortcut to storage! in Lakehouse1.
Which connection and endpoint should you specify? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:

When creating a shortcut to an Azure Data Lake Storage Gen2 account in a lakehouse, you should use the abfss (Azure Blob File System Secure) connection string and the dfs (Data Lake File System) endpoint. The abfss is used for secure access to Azure Data Lake Storage, and the dfs endpoint indicates that the Data Lake Storage Gen2 capabilities are to be used.
NEW QUESTION # 172
......
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