Question 1

You need to ensure the data loading activities in the AnalyticsPOC workspace are executed in the appropriate sequence. The solution must meet the technical
requirements.
What should you do?

Accepted Answer

To meet the technical requirement that data loading activities must ensure the raw and cleansed data is updated completely before populating the dimensional
model, you would need a mechanism that allows for ordered execution. A pipeline in Microsoft Fabric with dependencies set between activities can ensure that
activities are executed in a specific sequence. Once set up, the pipeline can be scheduled to run at the required intervals (hourly or daily depending on the data
source).

Question 2

What should you recommend using to ingest the customer data into the data store in the AnatyticsPOC workspace?

Accepted Answer

For ingesting customer data into the data store in the AnalyticsPOC workspace, a dataflow (D) should be recommended. Dataflows are designed within the Power
BI service to ingest, cleanse, transform, and load data into the Power BI environment. They allow for the low-code ingestion and transformation of data as needed
by Litware's technical requirements. References = You can learn more about dataflows and their use in Power BI environments in Microsoft's Power BI
documentation.

Question 3

You have a Fabric tenant that contains 30 CSV files in OneLake. The files are updated daily.
You create a Microsoft Power Bl semantic model named Modell that uses the CSV files as a data source. You configure incremental refresh for Model 1 and
publish the model to a Premium capacity in the Fabric tenant.
When you initiate a refresh of Model1, the refresh fails after running out of resources. What is a possible cause of the failure?

Accepted Answer

A possible cause for the failure is that query folding is NOT occurring (D). Query folding helps optimize refresh by pushing down the query logic to the source
system, reducing the amount of data processed and transferred, hence conserving resources. References = The Power BI documentation on incremental refresh
and query folding provides detailed information on this topic.

Question 4

You have a Fabric tenant that uses a Microsoft tower Bl Premium capacity. You need to enable scale-out for a semantic model. What should you do first?

Accepted Answer

To enable scale-out for a semantic model, you should first set Large dataset storage format to On (C) at the semantic model level. This configuration is necessary
to handle larger datasets effectively in a scaled-out environment. References = Guidance on configuring large dataset storage formats for scale-out is available in
the Power BI documentation.

Question 5

DRAG DROP - (Topic 2)
You have a Fabric tenant that contains a semantic model. The model contains data about retail stores.
You need to write a DAX query that will be executed by using the XMLA endpoint The query must return a table of stores that have opened since December
1,2023.

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How should you complete the DAX expression? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or
not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Accepted Answer

The correct order for the DAX expression would be:
? DEFINE VAR _SalesSince = DATE ( 2023, 12, 01 )
? EVALUATE
? FILTER (
? SUMMARIZE ( Store, Store[Name], Store[OpenDate] ),
? Store[OpenDate] >= _SalesSince )
In this DAX query, you're defining a variable _SalesSince to hold the date from which you want to filter the stores. EVALUATE starts the definition of the query. The
FILTER function is used to return a table that filters another table or expression. SUMMARIZE creates a
summary table for the stores, including the Store[Name] and Store[OpenDate] columns, and the filter expression Store[OpenDate] >= _SalesSince ensures only
stores opened on or after December 1, 2023, are included in the results.
References =
? DAX FILTER Function
? DAX SUMMARIZE Function

Question 6

HOTSPOT - (Topic 2)
You have a data warehouse that contains a table named Stage. Customers. Stage- Customers contains all the customer record updates from a customer
relationship management (CRM) system. There can be multiple updates per customer
You need to write a T-SQL query that will return the customer ID, name, postal code, and the last updated time of the most recent row for each customer ID.
How should you complete the code? To answer, select the appropriate options in the answer area,
NOTE Each correct selection is worth one point.

Accepted Answer

? In the ROW_NUMBER() function, choose OVER (PARTITION BY CustomerID ORDER BY LastUpdated DESC).
? In the WHERE clause, choose WHERE X = 1.
To select the most recent row for each customer ID, you use the ROW_NUMBER() window function partitioned by CustomerID and ordered by LastUpdated in
descending order. This will assign a row number of 1 to the most recent update for each customer. By selecting rows where the row number (X) is 1, you get the
latest update per customer. References =
? Use the OVER clause to aggregate data per partition
? Use window functions

Question 7

HOTSPOT - (Topic 2)
You have a Fabric warehouse that contains a table named Sales.Orders. Sales.Orders
contains the following columns.

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You need to write a T-SQL query that will return the following columns.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Accepted Answer

For the PeriodDate that returns the first day of the month for OrderDate, you should use DATEFROMPARTS as it allows you to construct a date from its individual
components (year, month, day).
For the DayName that returns the name of the day for OrderDate, you should use
DATENAME with the weekday date part to get the full name of the weekday. The complete SQL query should look like this:
SELECT OrderID, CustomerID,
DATEFROMPARTS(YEAR(OrderDate), MONTH(OrderDate), 1) AS PeriodDate, DATENAME(weekday, OrderDate) AS DayName
FROM Sales.Orders
Select DATEFROMPARTS for the PeriodDate and weekday for the DayName in the answer area.

Question 8

You have a Fabric notebook that has the Python code and output shown in the following exhibit.

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Which type of analytics are you performing?

Accepted Answer

The Python code and output shown in the exhibit display a histogram, which is a representation of the distribution of data. This kind of analysis is descriptive
analytics, which is used to describe or summarize the features of a dataset. Descriptive analytics answers the question of "what has happened" by providing insight
into past data through tools such as mean, median, mode, standard deviation, and graphical representations like histograms.
References: Descriptive analytics and the use of histograms as a way to visualize data distribution are basic concepts in data analysis, often covered in
introductory analytics and Python programming resources.

Question 9

You have a Fabric tenant that contains a warehouse.
Several times a day. the performance of all warehouse queries degrades. You suspect that Fabric is throttling the compute used by the warehouse.
What should you use to identify whether throttling is occurring?

Accepted Answer

To identify whether throttling is occurring, you should use the Monitoring hub (B). This provides a centralized place where you can monitor and manage the health,
performance, and reliability of your data estate, and see if the compute resources are being throttled. References = The use of the Monitoring hub for performance
management and troubleshooting is detailed in the Azure Synapse Analytics documentation.

Question 10

DRAG DROP - (Topic 2)
You are creating a dataflow in Fabric to ingest data from an Azure SQL database by using a T-SQL statement.
You need to ensure that any foldable Power Query transformation steps are processed by the Microsoft SQL Server engine.
How should you complete the code? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all.
You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Accepted Answer

You should complete the code as follows:
? Table
? NativeQuery
? EnableFolding
In Power Query, using Table before the SQL statement ensures that the result of the SQL query is treated as a table. NativeQuery allows a native database query
to be passed through from Power Query to the source database. The EnableFolding option ensures that any subsequent transformations that can be folded will be
sent back and executed at the source database (Microsoft SQL Server engine in this case).