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| Section | Weight | Objectives |
|---|---|---|
| Deploy and maintain a data solution | 10-15% | - Deploy data assets
|
| Secure and monitor data solutions | 15-20% | - Secure data solutions
|
| Clean, transform, and enrich data | 25-30% | - Enrich data
|
| Design and manage the data model | 20-25% | - Design a data model
|
| Load and prepare data | 20-25% | - Ingest data from source systems
|
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NEW QUESTION # 18
You have a Fabric warehouse that contains a table named Sales.Orders. Sales.Orders contains the following columns.
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.
Answer:
Explanation:
Explanation:
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.
NEW QUESTION # 19
You have a Fabric tenant that contains a warehouse.
You are designing a star schema model that will contain a customer dimension. The customer dimension table will be a Type 2 slowly changing dimension (SCD).
You need to recommend which columns to add to the table. The columns must NOT already exist in the source.
Which three types of columns should you recommend? Each correct answer presents part of the solution.
NOTE: Each correct answer is worth one point.
Answer: A,C,D
Explanation:
To create SCD type 2 one needs to add a surrogate key + start/end date beside the other technical attributes.
https://learn.microsoft.com/en-us/training/modules/populate-slowly-changing-dimensions-azure- synapse-analytics-pipelines/3-choose-between-dimension-types
NEW QUESTION # 20
You have a Microsoft Power Bl report named Report1 that uses a Fabric semantic model.
Users discover that Report1 renders slowly.
You open Performance analyzer and identify that a visual named Orders By Date is the slowest to render. The duration breakdown for Orders By Date is shown in the following table.
What will provide the greatest reduction in the rendering duration of Report1?
Answer: A
Explanation:
Based on the duration breakdown provided, the major contributor to the rendering duration is categorized as " Other, " which is significantly higher than DAX Query and Visual display times. This suggests that the issue is less likely with the DAX calculation or visual rendering times and more likely related to model performance or the complexity of the visual. However, of the options provided, optimizing the DAX query can be a crucial step, even if " Other " factors are dominant. Using DAX Studio, you can analyze and optimize the DAX queries that power your visuals for performance improvements. Here's how you might proceed:
Open DAX Studio and connect it to your Power BI report.
Capture the DAX query generated by the Orders By Date visual.
Use the Performance Analyzer feature within DAX Studio to analyze the query.
Look for inefficiencies or long-running operations.
Optimize the DAX query by simplifying measures, removing unnecessary calculations, or improving iterator functions.
Test the optimized query to ensure it reduces the overall duration.
References: The use of DAX Studio for query optimization is a common best practice for improving Power BI report performance as outlined in the Power BI documentation.
NEW QUESTION # 21
You have a Microsoft Power Bl semantic model that contains a table named Date. Date contains the following data.
You need to ensure that the visuals that use the Date table appear in chronological order. The solution must minimize administrative effort.
What should you do?
Answer: C
NEW QUESTION # 22
You have a Fabric tenant.
You are creating a Fabric Data Factory pipeline.
You have a stored procedure that returns the number of active customers and their average sales for the current month.
You need to add an activity that will execute the stored procedure in a warehouse. The returned values must be available to the downstream activities of the pipeline.
Which type of activity should you add?
Answer: B
Explanation:
In a Fabric Data Factory pipeline, to execute a stored procedure and make the returned values available for downstream activities, the Lookup activity is used. This activity can retrieve a dataset from a data store and pass it on for further processing. Here's how you would use the Lookup activity in this context:
* Add a Lookup activity to your pipeline.
* Configure the Lookup activity to use the stored procedure by providing the necessary SQL statement or stored procedure name.
* In the settings, specify that the activity should use the stored procedure mode.
* Once the stored procedure executes, the Lookup activity will capture the results and make them available in the pipeline's memory.
* Downstream activities can then reference the output of the Lookup activity.
References: The functionality and use of Lookup activity within Azure Data Factory is documented in Microsoft's official documentation for Azure Data Factory, under the section for pipeline activities.
NEW QUESTION # 23
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