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Reliable PL-300 Test Camp | PL-300 Exam Topic

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Microsoft PL-300 Exam is ideal for individuals who are looking to work as data analysts or business analysts. PL-300 exam is designed to test the candidates’ competency in creating, managing and interpreting data models with Power BI. Candidates will be required to have a strong understanding of Power BI features and functionality, data modeling techniques, and how to work with and manipulate data.

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The Microsoft Power BI Data Analyst Certification Exam will help you prepare for the new job role of a data analyst. A certified Data Analyst can use this exam to prove their skills in using Power BI to analyze business data, generate insightful visualizations, and share them with customers. Microsoft PL-300 Dumps is designed to test your knowledge of business data modeling, data analysis and visualization, and dashboard development in Power BI. The exam will cover the following topics:

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Microsoft Power BI Data Analyst Sample Questions (Q135-Q140):

NEW QUESTION # 135
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
From Power Query Editor, you profile the data shown in the following exhibit.

The IoT GUID and IoT ID columns are unique to each row in query.
You need to analyze IoT events by the hour and day of the year. The solution must improve dataset performance.
Solution: You split the loT DateTime column into a column named Date and a column named Time.
Does this meet the goal?

A. Yes
B. No

Answer: B

NEW QUESTION # 136
Note: This question is a part of a series of questions that present the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
Start of repeated scenario
You have a Microsoft SQL Server database that has the tables shown in the Database Diagram exhibit. (Click the Exhibit.)

You plan to develop a Power BI model as shown in the Power BI Model exhibit. (Click the Exhibit).

You plan to use Power BI to import data from 2013 to 2015.
Product Subcategory [Subcategory] contains NULL values.
End of repeated scenario.
You implement the Power BI model.
You add another table named Territory to the model. A sample of the data is shown in the following table.

You need to create a relationship between the Territory table and the Sales table.
Which function should you use in the query for Territory before you create the relationship?

A. Table.RemoveMatchingRows
B. Table.InDistinct
C. Table.Distinct
D. Table.ReplaceMatchingRows

Answer: C

Explanation:
Explanation
References: https://msdn.microsoft.com/en-us/library/mt260775.aspx

NEW QUESTION # 137
You receive revenue data that must be included in Microsoft Power Bl reports.
You perform an initial load of the data from a Microsoft Excel source as shown in the following exhibit.

You plan to create several visuals from the data, including a visual that shows revenue split by year and product.
You need to transform the data to ensure that you can build the visuals. The solution must ensure that the columns are named appropriately for the data that they contain.
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
Text Description automatically generated with medium confidence

Step 1: Select Use Header as First Row.
Step 2: Select Department and Product and Unpivot Other Columns
Unpivot Other Columns: This command unpivots unselected columns. Use this command in a query when not all columns are known. New columns added during a refresh operation are also unpivoted.
Step 3: Rename the Attribute column to Year and the Value column to Revenue.
You might want to unpivot data, sometimes called flattening the data, to put it in a matrix format so that all similar values are in one column. This is necessary, for example, to create a chart or a report.
Chart Description automatically generated with medium confidence

When you unpivot, you unpack the attribute-value pairs that represent an intersection point of the new columns and re-orient them into flattened columns:
Values (in blue on the left) are unpivoted into a new column (in blue on the right).
Attributes (in green on the left) are unpivoted into a new column (in green on the right) and duplicates are correspondingly mapped to the new Values column.
Reference:
https://support.microsoft.com/en-us/office/unpivot-columns-power-query-0f7bad4b-9ea1-49c1-9d95-f588221c70

NEW QUESTION # 138
You need to create a visual as shown in the following exhibit.

The indicator color for Total Sales will be based on % Growth to Last Year.
The solution must use the existing calculations only.
How should you configure the visual? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
Box 1: Background color
To format the Color column based on its field values, select Conditional formatting for the Color field, and then select Background color or Font color.
In the Background color or Font color dialog box, select Field value from the Format by drop-down field.
Box 2: Field value
With conditional formatting for tables in Power BI Desktop, you can specify customized cell colors, including color gradients, based on field values.
Reference:
https://docs.microsoft.com/en-us/power-bi/create-reports/desktop-conditional-table-formatting

NEW QUESTION # 139
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is the same in each question in this series.
You have a Microsoft SQL Server database that contains the following tables.

The following columns contain date information:
- Date[Month] in the mmyyyy format
- Date[Date_ID] in the ddmmyyyy format
- Date[Date_name] in the mm/dd/yyyy format
- Monthly_returns[Month_ID] in the mmyyyy format
The Order table contains more than one million rows.
The Store table has a relationship to the Monthly_returns table on the Store_ID column. This is the only relationship between the tables.
You plan to use Power BI Desktop to create an analytics solution for the data.
You need to create a relationship between the Order table and the Store table on the Store_ID column.
What should you do before you create the relationship?

A. In the Order table query, use the Table.TrasformColumnTypes function.
B. In the Store table query, use the Table.TrasformColumnTypes function.
C. In the Store table query, use the Table.TrasformRows function.
D. In the Order table query, use the Table.TrasformRows function.

Answer: B

NEW QUESTION # 140
......

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