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| Topic | Details |
|---|
| 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.
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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 | - 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 (Q151-Q156):
NEW QUESTION # 151
You have source data in a folder on a local computer.
You need to create a solution that will use Fabric to populate a data store. The solution must meet the following requirements:
* Support the use of dataflows to load and append data to the data store.
* Ensure that Delta tables are V-Order optimized and compacted automatically.
Which type of data store should you use?
- A. a warehouse
- B. a KQL database
- C. an Azure SQL database
- D. a lakehouse
Answer: A,C
Explanation:
A lakehouse (A) is the type of data store you should use. It supports dataflows to load and append data and ensures that Delta tables are Z-Order optimized and compacted automatically. Reference = The capabilities of a lakehouse and its support for Delta tables are described in the lakehouse and Delta table documentation.
NEW QUESTION # 152
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 customer 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?
- A. The CustomerKey column in FactTransaction and a relationship to DimCustomer
- B. A many-to-many relationship between FactTransaction and DimCustomer
- C. A bridge table with relationships to FactTransaction and DimCustomer
- D. A bridge table with relationships to DimCustomer and DimAccount
Answer: D
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 .
NEW QUESTION # 153
You have a Fabric tenant that contains a semantic model named Model1. Model1 contains a fact table named FactSales. FactSales has a relationship to a dimension table named DimDate on a column named OrderDate.
To FactSales, you add a second relationship between FactSales and DimDate based on a column named ShippedDate.
You need to filter by using ShippedDate in a new report. The solution must NOT affect the function of existing reports.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct answer is worth one point.
- A. Enable the ShippedDate relationship.
- B. Use a USERELATIONSHIP DAX function.
- C. Disable the ShippedDate relationship between the tables.
- D. Use a CROSSFILTER DAX function.
- E. Use a RELATEDTABLE DAX function.
Answer: B,C
Explanation:
To use the ShippedDate relationship without breaking existing reports, you must treat the second relationship as inactive and invoke it specifically within a DAX measure.
[E]
Step 1: Configure the Relationship
The most important step for backward compatibility is ensuring the new relationship does not become the "Active" path.
Open your Model View in Power BI Desktop or the Fabric Web UI.
Locate the relationship between FactTable[ShippedDate] and DimDate[OrderDate].
Right-click the relationship and select Properties.
Uncheck the box "Make this relationship active."
Ensure the existing relationship (OrderDate) remains Active.
[D]
Step 2: Create the DAX Measure
Because the relationship is inactive, standard filters on the Date table will only affect OrderDate.
To filter by ShippedDate, you must create a measure that explicitly activates that path.
Total Sales by Shipped Date =
CALCULATE(
[Total Sales],
USERELATIONSHIP(FactTable[ShippedDate], DimDate[DateKey])
)
Incorrect:
[Not A]
Do not make the ShippedDate relationship active: This will immediately break all existing reports that expect the OrderDate relationship to be the default.
[Not C]
Do not use bi-directional filters: This does not solve the multiple-date problem and can cause performance issues or ambiguity.
Reference:
https://sergiomurru.com/2021/02/19/ambiguous-model-and-userelationship/
NEW QUESTION # 154
You have a Fabric tenant that contains a workspace named Workspace1 and a user named User1. Workspace1 contains a warehouse named DW1.
You share DW1 with User1 and assign User1 the default permissions for DW1.
What can User1 do?
- A. Read data from the tables in DW1.
- B. Read the underlying Parquet files from OneLake.
- C. Connect to DW1 via the Azure SQL Analytics endpoint.
- D. Build reports by using the default dataset.
Answer: D
Explanation:
If no additional permissions are selected - The shared recipient by default receives "Read" permission, which only allows the recipient to connect to the SQL analytics endpoint.
https://learn.microsoft.com/en-us/fabric/data-warehouse/share-warehouse-manage- permissions#share-a-warehouse
NEW QUESTION # 155
You have a Fabric workspace named Workspace1.
Workspace1 contains multiple semantic models, including a model named Model1. Model1 is updated by using an XMLA endpoint.
You need to increase the speed of the write operations of the XMLA endpoint.
What should you do?
- A. Select Large semantic model storage format for Workspace1.
- B. Delete any unused columns from Model1.
- C. Delete any unused semantic models from Workspace1.
- D. Configure Model1 to use the Direct Lake storage format.
Answer: D
NEW QUESTION # 156
......
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