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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Visualize and analyze data | 25-35% | - Enhance reports for usability
|
| Topic 2: Model the data | 30-40% | - Design a data model
|
| Topic 3: Prepare the data | 15-20% | - Clean, transform, and load data
|
| Topic 4: Deploy and maintain assets | 15-20% | - Secure and monitor Power BI
|
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NEW QUESTION # 362
You have sales data in a star schema that contains four tables named Sales, Customer, Date, and Product.
The Sales table contains purchase and ship dates.
Most often, you will use the purchase date to analyze the data, but you will analyze the data by both dates independently and together.
You need to design an imported semantic model to support the analysis. The solution must minimize the model size and the number of queries against the data source.
Which data modeling design should you use?
Answer: A
Explanation:
The supported selection is C (On the Date table, use a reference query in Power Query and create active relationships between Sales and both Date tables in the modeling view). The key constraint is to design an imported semantic model to support the analysis. The solution must minimize the model size and the number of queries against the data source. Keeping hidden auto date/time tables alongside a marked common Date table adds redundant structures and inconsistent hierarchies. Auto date/time can create a hidden date table for every eligible date column. A single marked date table plus disabling auto date/time reduces those hidden structures while retaining reusable month and quarter attributes. In Microsoft ' s current exam outline, the corresponding objective is " Create a common date table " .
Microsoft Learn reference: https://learn.microsoft.com/en-us/power-bi/transform-model/desktop-auto-date- time | PL-300 objective: " Create a common date table " | Study guide: https://learn.microsoft.com/en-us
/credentials/certifications/resources/study-guides/pl-300
NEW QUESTION # 363
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.
You are modeling data by using Microsoft Power BI. Part of the data model is a large Microsoft SQL Server table named Order that has more than 100 million records.
During the development process, you need to import a sample of the data from the Order table.
Solution: You add a WHERE clause to the SQL statement.
Does this meet the goal?
Answer: A
Explanation:
Explanation
The WHERE clause has its effects before the data is imported.
Reference:
https://docs.microsoft.com/en-us/power-bi/connect-data/service-gateway-sql-tutorial
NEW QUESTION # 364
You hove a folder that contains 50 JSON files.
You need to use Power 81 Desktop to make the metadata ol the files available as a single semantic model.
The solution must NOT store the data of the JSON files.
Which type of data source should you use. and which transformation should you perform? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 365
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 need to add a new column to the Product Subcategory table that uses the following formula.
=if [Subcategory] =null then "NA" else [Subcategory]
Which command should you use in Query Editor?
Answer: D
Explanation:
The technical decision turns on how to add a new column to the Product Subcategory table that uses the following formula. =if [Subcategory] =null then "NA" else [Subcategory] . The verified answer is B (Custom Column). The M transformation belongs in the query pipeline, where source values can be cleaned, split, filled, renamed, or typed consistently. A report visual or DAX measure would operate too late in the process.
A visual, measure, or model relationship cannot repair the incoming tabular shape; those features operate after the query result has already been loaded. The current PL-300 study guide places this under the objective " Resolve inconsistencies, unexpected or null values, and data quality issues " .
Microsoft Learn reference: https://learn.microsoft.com/en-us/power-query/best-practices | PL-300 objective: " Resolve inconsistencies, unexpected or null values, and data quality issues " | Study guide: https://learn.
microsoft.com/en-us/credentials/certifications/resources/study-guides/pl-300
NEW QUESTION # 366
Hotspot Question
You have a Power BI report that contains a measure named Total Sales.
You need to create a new measure that will return the sum of Total Sales for a year up to a selected date.
How should you complete the DAX expression? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: TOTALYTD
TOTALYTD evaluates the specified expression over the interval which begins on the first day of the year and ends with the last date in the specified date column after applying specified filters.
Syntax: TOTALYTD (
<Expression>,
<Dates>
[, <Filter>]
[, <YearEndDate>]
Expression - The expression to be evaluated.
Dates - The name of a column containing dates or a one column table containing dates.
Example:
TOTALYTD ( -- 2007-01-01 : 2007-05-12
[Sales Amount],
'Date'[Date]
Box 2: 'Date'[Date]
Reference:
https://dax.guide/totalytd/
NEW QUESTION # 367
......
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