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NEW QUESTION # 198
You have an Azure SQL database named DB1 and a Fabric workspace named Workspace1.
Workspace1 contains a lakehouse named LH1 and a Dataflow Gen2 named Dataflow1.
Dataflow1 includes a query named Query1 that loads data from DB1, applies transformations to the data, and then filters the data.
You discover that Query1 loads all the data before applying the transformations.
You need to ensure that Query1 uses query folding.
What should you do?
Answer: C
Explanation:
To ensure your Dataflow Gen2 query uses query folding when loading from Azure SQL to a Lakehouse, you need to verify that your transformations are being translated into a single SQL statement that is executed by the source database. This prevents the "load all data" behavior you are currently experiencing.
Rearrange Transformations
Power Query stops folding once it hits a step it cannot translate into SQL. To maximize efficiency:
Filter and Select early: Always place Filter Rows and Choose Columns steps as early as possible. This ensures only necessary data is retrieved from Azure SQL.
Reference:
https://www.linkedin.com/posts/salina-bagwan-1007471b6_qliksense-qlikinterviewquestions- sqlinterviewquestions-activity-7311428148225568769-LDMw
NEW QUESTION # 199
You have a Fabric tenant that contains a workspace named Workspace! Workspace1 uses the Pro license mode and contains a semantic model named Model1.
You have an Azure DevOps organization.
You need to enable version control for Workspace1. The solution must ensure that Model 1 is added to the repository.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
We need to enable version control for a Fabric workspace (Workspace1) and ensure that Model1 (a semantic model) is added to an Azure DevOps repository.
Key facts:
Workspace1 is in Pro mode. To enable Git integration, the workspace must be assigned to a Fabric capacity.
Git integration steps in Fabric:
Assign the workspace to a Fabric capacity.
Connect the workspace to a Git provider (e.g., Azure DevOps or GitHub).
Sync the workspace with the repository (to push artifacts like semantic models).
Branch policies and deployment pipelines are not needed for simply enabling version control.
Correct Sequence:
Assign Workspace1 to a Fabric capacity.
Connect Workspace1 to a Git provider.
Sync Workspace1 with the repository.
Final Answer:
Step 1 # Assign Workspace1 to a Fabric capacity
Step 2 # Connect Workspace1 to a Git provider
Step 3 # Sync Workspace1 with the repository
References:
Microsoft Fabric Git integration
Enable Git in Fabric workspace
This ensures Model1 will be version-controlled in the linked DevOps repository.
NEW QUESTION # 200
You have a Fabric workspace that contains a warehouse named Warehouse!. Warehousel contains the following data.
You need to create a T-SQL statement that will denormalize the tables and include the ContractType and StartDate attributes in the results. The solution must meet the following requirements:
* Include attributes from matching rows in the Contract table.
* Ensure that all the rows from the Employee table are preserved.
* Return the total number of employees per contract type for all the contract types that have more than two employees.
How should you complete the statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Comprehensive Detailed Explanation
We are tasked with writing a T-SQL query to denormalize the tables Employee and Contract in a Fabric warehouse.
Requirements Breakdown
Include attributes from matching rows in the Contract table
This means we must join Employee and Contract on EmployeeID .
Ensure that all rows from the Employee table are preserved
This requires a LEFT OUTER JOIN from Employee to Contract. If an employee has no contract, we still want the employee record included.
Return the total number of employees per contract type for all contract types that have more than two employees This means we need to:
Group by ContractType
Count distinct EmployeeID
Filter groups where that count > 2.
To filter aggregated results, we use HAVING , not WHERE.
Completed Query
WITH result AS (
SELECT
e.EmployeeID,
e.EmployeeName,
e.EmployeePosition,
c.ContractType,
c.StartDate
FROM Employee AS e
LEFT OUTER JOIN Contract AS c
ON c.EmployeeID = e.EmployeeID
)
SELECT
ContractType,
COUNT ( DISTINCT EmployeeID) AS TotalEmployees
FROM result
GROUP BY ContractType
HAVING COUNT ( DISTINCT EmployeeID) > 2 ;
Why This is Correct
LEFT OUTER JOIN ensures all employees are included, regardless of contracts.
HAVING allows filtering aggregated groups by employee counts.
The query returns ContractType , StartDate (as requested in denormalization), and aggregated employee counts.
References
T-SQL JOINs in Microsoft Fabric
Aggregate functions and HAVING clause
Denormalization best practices in Fabric warehouses
NEW QUESTION # 201
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.
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 # 202
You have a Fabric tenant that contains two workspaces named Workspace1 and Workspace2.
Workspace1 is used as the development environment.
Workspace2 is used as the production environment.
Each environment uses a different storage account.
Workspace1 contains a Dataflow Gen2 named Dataflow1. The data source of Dataflow1 is a CSV file in blob storage.
You plan to implement a deployment pipeline to deploy items from Workspace1 to Workspace2.
You need to ensure that the data source references the correct location in the production environment.
What should you do?
Answer: A
Explanation:
Scenario:
Dev = Workspace1 with Dataflow Gen2 (source = blob storage CSV).
Prod = Workspace2, different storage account.
Need: ensure deployed dataflow points to the production storage location .
Analysis:
Data source rules : used to remap data sources between environments (e.g., blob storage dev # blob storage prod).
Parameter rules : used when the data source location is parameterized (for example, a parameter storing the file path or connection string).
Best practice: use parameters in the dataflow for connection strings, then apply parameter rules in deployment pipelines.
In this case, since the requirement is about ensuring the reference updates correctly, only parameter rules are needed (not data source rules).
.
NEW QUESTION # 203
......
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