Free DP-500 Exam Braindumps (page: 18)

Page 18 of 46

DRAG DROP (Drag and Drop is not supported)
You are using DAX Studio to query an XMLA endpoint.

You need to identify the duplicate values in a column named Email in a table named Subscription.

How should you complete the DAX expression? To answer, drag the appropriate values to the 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.
Select and Place:

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Box 1: CALCULATE

Box 2: CURRENTGROUP
CURRENTGROUP returns a set of rows from the table argument of a GROUPBY expression that belong to the current row of the GROUPBY result.

Remarks
This function can only be used within a GROUPBY expression.

This function takes no arguments and is only supported as the first argument to one of the following aggregation functions: AVERAGEX, COUNTAX, COUNTX, GEOMEANX, MAXX, MINX, PRODUCTX, STDEVX.S, STDEVX.P, SUMX, VARX.S, VARX.P.

Note: COUNTX counts the number of rows that contain a non-blank value or an expression that evaluates to a non-blank value, when evaluating an expression over a table.


Reference:

https://docs.microsoft.com/en-us/dax/currentgroup-function-dax



You have a Power BI report that contains one visual.

You need to provide users with the ability to change the visual type without affecting the view for other users.

What should you do?

  1. From Tabular Editor, create a new perspective.
  2. From Visual options in Report settings, select Use the modern visual header with updated styling options.
  3. From Report setting, select Personalize visuals.
  4. From the Bookmarks pane, select Focus mode, and then select Add.

Answer(s): C

Explanation:

Enable personalization in a report
You can enable the feature either in Power BI Desktop or the Power BI service. You can also enable it in embedded reports.

To enable the feature in Power BI Desktop, go to File > Options and settings > Options > Current file > Report settings. Make sure Personalize visuals is turned on.

Incorrect:
Not A: A perspective is a view of the model. It allows you to maintain your Shared Dataset (often called a Golden Dataset from this blog post); but, presents a smaller view to the consumers so they are not overwhelmed with tables, columns, and measures they don’t need.


Reference:

https://docs.microsoft.com/en-us/power-bi/create-reports/power-bi-personalize-visuals?tabs=powerbi-desktop#enable-personalization-in-a-report



You have a kiosk that displays a Power BI report page. The report uses a dataset that uses Import storage mode.

You need to ensure that the report page updates all the visuals every 30 minutes.

Which two actions should you perform? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

  1. Configure the data sources to use DirectQuery.
  2. Select Auto page refresh.
  3. Enable Power BI embedded.
  4. Enable the XMLA endpoint.
  5. Add a Microsoft Power Automate visual to the report page.
  6. Configure the data sources to use a streaming dataset.

Answer(s): A,B

Explanation:

Automatic page refresh in Power BI enables your active report page to query for new data, at a predefined cadence, for DirectQuery sources.

Automatic page refresh is available for DirectQuery sources and some LiveConnect scenarios, so it will only be available when you are connected to a supported data source. This restriction applies to both automatic page refresh types.


Reference:

https://docs.microsoft.com/en-us/power-bi/create-reports/desktop-automatic-page-refresh



You are using a Python notebook in an Apache Spark pool in Azure Synapse Analytics.

You need to present the data distribution statistics from a DataFrame in a tabular view.

Which method should you invoke on the DataFrame?

  1. rollup
  2. freqItems
  3. explain
  4. describe

Answer(s): D

Explanation:

The aggregating statistic can be calculated for multiple columns at the same time with the describe function.

Example:
titanic[["Age", "Fare"]].describe()
Out[6]:
Age Fare
count 714.000000 891.000000
mean 29.699118 32.204208
std 14.526497 49.693429
min 0.420000 0.000000
25% 20.125000 7.910400
50% 28.000000 14.454200
75% 38.000000 31.000000
max 80.000000 512.329200


Reference:

https://pandas.pydata.org/docs/getting_started/intro_tutorials/06_calculate_statistics.html



Page 18 of 46



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