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DP-600 New Dumps Book, DP-600 Vce Free

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Microsoft DP-600 Exam Syllabus Topics:

Topic
Details

Topic 1

Implement and manage semantic models: The topic delves into designing and building semantic models, and optimizing enterprise-scale semantic models.

Topic 2

Maintain a data analytics solution: This section is all about implementing security and governance. In this topic, you also get information about maintaining the analytics development lifecycle.

Topic 3

Prepare data: In this topic, questions about creating objects in a lakehouse or warehouse, copying data, transforming data, and optimizing performance appear.

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DP-600 Vce Free, DP-600 Certification Training

The Microsoft DP-600 certification verifies that you have a basic understanding of Implementing Analytics Solutions Using Microsoft Fabric concepts and virtualization. Success in the DP-600 exam of the Microsoft DP-600 certificate also proves your knowledge of basic troubleshooting concepts and data center technology. When you earn the DP-600 Certification you will get reliable exam guide materials.

Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q19-Q24):

NEW QUESTION # 19
You have a Fabric tenant that contains a lakehouse named Lakehouse1. Lakehouse1 contains a table named Nyctaxi_raw. Nyctaxi_raw contains the following columns.

You create a Fabric notebook and attach it to lakehouse1.
You need to use PySpark code to transform the data. The solution must meet the following requirements:
* Add a column named pickupDate that will contain only the date portion of pickupDateTime.
* Filter the DataFrame to include only rows where fareAmount is a positive number that is less than 100.
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:

* Add the pickupDate column: .withColumn("pickupDate", df["pickupDateTime"].cast("date"))
* Filter the DataFrame: .filter("fareAmount > 0 AND fareAmount < 100")
In PySpark, you can add a new column to a DataFrame using the .withColumn method, where the first argument is the new column name and the second argument is the expression to generate the content of the new column. Here, we use the .cast("date") function to extract only the date part from a timestamp. To filter the DataFrame, you use the .filter method with a condition that selects rows where fareAmount is greater than 0 and less than 100, thus ensuring only positive values less than 100 are included.

NEW QUESTION # 20
You have a Microsoft Power B1 Premium Per User (PPU) workspace that contains a semantic model.
You have an Azure App Service app named App1 that modifies row-level security (RLS) for the model by using the XMLA endpoint. App1 requires users to sign in by using their Microsoft Entra credentials to access the XMLA endpoint. You need to configure App1 to use a service account to access the model. What should you do first?

A. Upgrade the workspace to Premium capacity.
B. Add a managed identity to the workspace.
C. Modify the XMLA Endpoint setting.
D. Add a managed identity to App1.

Answer: D

NEW QUESTION # 21
You have a query in Microsoft Power BI Desktop that contains two columns named Order_Date and Shipping_Date.
You need to create a column that will calculate the number of days between Order_Date and Shipping_Date for each row.
Which Power Query function should you use?

A. Date.AddDays
B. DateTime.LocalNow
C. Duration.Days
D. Duration.From

Answer: C

NEW QUESTION # 22
You have a custom Direct Lake semantic model named Model1 that has one billion rows of data.
You use Tabular Editor to connect to Model1 by using the XMLA endpoint.
You need to ensure that when users interact with reports based on Model1, their queries always use Direct Lake mode.
What should you do?

A. From Model, configure the Direct Lake Behavior option.
B. From Model, configure the Default Mode option.
C. From Model, configure the Storage Location option.
D. From Partitions, configure the Mode option.

Answer: A

Explanation:
Click on Semantic model.
In the Properties pane, choose the Direct Lake behavior for your custom Direct Lake semantic model:
Automatic: This is the default behavior. It allows Direct Lake with fallback to DirectQuery mode if data can't be efficiently loaded into memory.
Direct Lake only: This option ensures no fallback to DirectQuery mode
https://powerbi.microsoft.com/en-au/blog/leveraging-pure-direct-lake-mode-for-maximum-query- performance/

NEW QUESTION # 23
You have a Fabric tenant that contains two lakehouses.
You are building a dataflow that will combine data from the lakehouses. The applied steps from one of the queries in the dataflow is shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic. NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Folding in Power Query refers to operations that can be translated into source queries. In this case, "some" of the steps can be folded, which means that some transformations will be executed at the data source level. The steps that cannot be folded will be executed within the Power Query engine. Custom steps, especially those that are not standard query operations, are usually executed within Power Query engine rather than being pushed down to the source system.
References =
* Query folding in Power Query
* Power Query M formula language

NEW QUESTION # 24
......

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