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?
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.
Reference
Manage object-level security in Microsoft Fabric warehouses
You have a Fabric tenant that contains a semantic model named Model1. Model1 uses Import mode. Model1 contains a table named Orders. Orders has 100 million rows and the following fields.

You need to reduce the memory used by Model! and the time it takes to refresh the model. Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct answer is worth one point.
To reduce memory usage and refresh time, splitting the OrderDateTime into separate date and time columns (A) can help optimize the model because date/time data types can be more memory-intensive than separate date and time columns. Moreover, replacing TotalSalesAmount with a measure (D) instead of a calculated column ensures that the calculation is performed at query time, which can reduce the size of the model as the value is not stored but calculated on the fly. Reference = The best practices for optimizing Power BI models are detailed in the Power BI documentation, which recommends using measures for calculations that don't need to be stored and adjusting data types to improve performance.
You have a Fabric tenant that contains a warehouse named DW1 and a lakehouse named LH1. DW1 contains a table named Sales.Product. LH1 contains a table named Sales.Orders.
You plan to schedule an automated process that will create a new point-in-time (PIT) table named Sales.ProductOrder in DW1. Sales.ProductOrder will be built by using the results of a query that will join Sales.Product and Sales.Orders.
You need to ensure that the types of columns in Sales. ProductOrder match the column types in the source tables. The solution must minimize the number of operations required to create the new table.
Which operation should you use?
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?
When using XMLA endpoints to manage and update semantic models in Microsoft Fabric, the performance of write operations (such as processing, structural changes, or metadata deployments from Tabular Editor) is directly influenced by the storage format and how the model is persisted.
Why Option A is Correct
By default, Fabric semantic models use the Small semantic model storage format.
To improve write operations performance through XMLA, you must change the workspace setting to use the Large semantic model storage format.
The large format uses more efficient storage techniques, supports partitioning, and handles larger models with optimized write capabilities.
This setting is applied at the workspace level and impacts all semantic models within that workspace, including Model1.
This is explicitly documented in Microsoft's guidance: Large semantic model storage format is required when using XMLA write operations for large or frequently updated models.
Why the Other Options Are Incorrect
B . Configure Model1 to use the Direct Lake storage format.
Direct Lake mode is designed for query performance (reading data directly from OneLake in delta format without import/duplication).
It improves query latency and freshness but does not improve XMLA write operations, which deal with model metadata and structural updates.
C . Delete any unused semantic models from Workspace1.
Deleting unused semantic models helps manage capacity and storage but does not increase the speed of XMLA endpoint write operations.
Workspace storage overhead does not directly impact the write throughput of XMLA operations.
D . Delete any unused columns from Model1.
Removing unused columns reduces the memory footprint and can improve query performance.
However, it does not directly improve the speed of XMLA write operations. The bottleneck in XMLA writes is tied to the storage format, not the model size alone.
Summary
To increase the speed of XMLA write operations on semantic models, you must enable the Large semantic model storage format at the workspace level. This setting ensures better handling of writes and metadata operations via the XMLA endpoint.
Reference
Large models in Power BI and Microsoft Fabric
Use the XMLA endpoint in Microsoft Fabric
You are creating a semantic model in Microsoft Power Bl Desktop.
You plan to make bulk changes to the model by using the Tabular Model Definition Language (TMDL) extension for Microsoft Visual Studio Code.
You need to save the semantic model to a file.
Which file format should you use?
When saving a semantic model to a file that can be edited using the Tabular Model Scripting Language (TMSL) extension for Visual Studio Code, the PBIX (Power BI Desktop) file format is the correct choice. The PBIX format contains the report, data model, and queries, and is the primary file format for editing in Power BI Desktop. Reference = Microsoft's documentation on Power BI file formats and Visual Studio Code provides further clarification on the usage of PBIX files.
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