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Actualkey Prepration Latest PL-300 : Microsoft Power BI Data Analyst Exam Questions and Answers PDF's, Verified Answers via Experts - Pass Your Exam For Sure and instant Downloads - "Money Back Guarantee".
| Vendor | Microsoft |
| Certification | Microsoft Certified: Power BI Data Analyst Associate |
| Exam Code | PL-300 |
| Title | Microsoft Power BI Data Analyst Exam |
| No Of Questions | 373 |
| Last Updated | September 17,2024 |
| Product Type | Q & A with Explanation |
| Bundel Pack Included | PDF + Offline / Andriod Testing Engine and Simulator |
Power Platform Overview:
Understanding the components of Power Platform: Power BI, Power Apps, Power Automate, and Power Virtual Agents.
Power Apps:
Canvas Apps vs. Model-Driven Apps.
Building and designing Power Apps.
Data sources and connections.
Power Automate:
Workflow automation.
Creating flows.
Integration with other Microsoft and third-party services.
Power BI:
Creating reports and dashboards.
Data visualization.
Power Query and Data Modeling.
Power Virtual Agents:
Creating chatbots.
Integration with other Power Platform components.
Common Data Service (CDS):
Understanding and working with CDS.
Entities, relationships, and data modeling.
Security and Governance:
Implementing security measures.
Managing access and permissions.
Administration and Deployment:
Lifecycle management.
Environment management.
Remember, these are general areas that may be covered in the PL-300 exam. For the most accurate and up-to-date information, it's recommended to refer to the official Microsoft documentation and the skills measured section on the exam page.
Updates to the exam
Our exams are updated periodically to reflect skills that are required to perform a role. We have included two versions of the Skills Measured objectives depending on when you are taking the exam.
We always update the English language version of the exam first. Some exams are localized into other languages, and those are updated approximately eight weeks after the English version is updated. Although Microsoft makes every effort to update localized versions as noted, there may be times when the localized versions of an exam are not updated on this schedule. Other available languages are listed in the Schedule Exam section of the Exam Details webpage. If the exam isn't available in your preferred language, you can request an additional 30 minutes to complete the exam.
Note
The bullets that follow each of the skills measured are intended to illustrate how we are assessing that skill. Related topics may be covered in the exam.
Note
Most questions cover features that are general availability (GA). The exam may contain questions on Preview features if those features are commonly used.
Skills measured as of February 6, 2024
Audience profile
As a candidate for this exam, you should deliver actionable insights by working with available data and applying domain expertise. You should:
Provide meaningful business value through easy-to-comprehend data visualizations.
Enable others to perform self-service analytics.
Deploy and configure solutions for consumption.
As a Power BI data analyst, you work closely with business stakeholders to identify business requirements. You collaborate with enterprise data analysts and data engineers to identify and acquire data. You use Power BI to:
Transform the data.
Create data models.
Visualize data.
Share assets.
You should be proficient at using Power Query and writing expressions by using Data Analysis Expressions (DAX). You know how to assess data quality. Plus, you understand data security, including row-level security and data sensitivity.
Skills at a glance
Prepare the data (25–30%)
Model the data (25–30%)
Visualize and analyze the data (25–30%)
Deploy and maintain items (15–20%)
Prepare the data (25–30%)
Get data from data sources
Identify and connect to a data source
Change data source settings, including credentials, privacy levels, and data source locations
Select a shared semantic model, or create a local data model
Choose between DirectQuery, Import, and Dual mode
Change the value in a parameter
Clean the data
Evaluate data, including data statistics and column properties
Resolve inconsistencies, unexpected or null values, and data quality issues
Resolve data import errors
Transform and load the data
Select appropriate column data types
Create and transform columns
Transform a query
Design a star schema that contains facts and dimensions
Identify when to use reference or duplicate queries and the resulting impact
Merge and append queries
Identify and create appropriate keys for relationships
Configure data loading for queries
Model the data (25–30%)
Design and implement a data model
Configure table and column properties
Implement role-playing dimensions
Define a relationship's cardinality and cross-filter direction
Create a common date table
Implement row-level security roles
Create model calculations by using DAX
Create single aggregation measures
Use CALCULATE to manipulate filters
Implement time intelligence measures
Identify implicit measures and replace with explicit measures
Use basic statistical functions
Create semi-additive measures
Create a measure by using quick measures
Create calculated tables
Optimize model performance
Improve performance by identifying and removing unnecessary rows and columns
Identify poorly performing measures, relationships, and visuals by using Performance Analyzer
Improve performance by choosing optimal data types
Improve performance by summarizing data
Visualize and analyze the data (25–30%)
Create reports
Identify and implement appropriate visualizations
Format and configure visualizations
Use a custom visual
Apply and customize a theme
Configure conditional formatting
Apply slicing and filtering
Configure the report page
Use the Analyze in Excel feature
Choose when to use a paginated report
Enhance reports for usability and storytelling
Configure bookmarks
Create custom tooltips
Edit and configure interactions between visuals
Configure navigation for a report
Apply sorting
Configure sync slicers
Group and layer visuals by using the Selection pane
Drill down into data using interactive visuals
Configure export of report content, and perform an export
Design reports for mobile devices
Identify patterns and trends
Use the Analyze feature in Power BI
Use grouping, binning, and clustering
Incorporate the Q&A feature in a report
Use AI visuals
Use reference lines, error bars, and forecasting
Detect outliers and anomalies
Create and share scorecards and metrics
Deploy and maintain items (15–20%)
Create and manage workspaces and items
Create and configure a workspace
Assign workspace roles
Configure and update a workspace app
Publish, import, or update items in a workspace
Create dashboards
Choose a distribution method
Apply sensitivity labels to workspace content
Configure subscriptions and data alerts
Promote or certify Power BI content
Manage global options for files
Manage semantic models
Identify when a gateway is required
Configure a semantic model scheduled refresh
Configure row-level security group membership
Provide access to semantic models
Sample Questions and Answers
Version: 13.0
New Topic: Topic 1, Litware, Inc. Case Study
Overview
This is a case study. Case studies are not timed separately. You can use as much exam time as you
would like to complete each case. However, there may be additional case studies and sections on
this exam. You must manage your time to ensure that you are able to complete all questions included
on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is
provided in the case study. Case studies might contain exhibits and other resources that provide
more information about the scenario that is described in the case study. Each question is
independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your
answers and to make changes before you move to the next section of the exam. After you begin a
new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane
to explore the content of the case study before you answer the questions. Clicking these buttons
displays information such as business requirements, existing environment and problem statements.
If the case study has an All Information tab, note that the information displayed is identical to the
information displayed on the subsequent tabs. When you are ready to answer a question, click the
Question button to return to the question.
Overview
Litware, Inc. is an online retailer that uses Microsoft Power Bl dashboards and reports.
The company plans to leverage data from Microsoft SQL Server databases, Microsoft Excel files, text
files, and several other data sources.
Litware uses Azure Active Directory (Azure AD) to authenticate users.
- Existing Environment
Sales Data
Litware has online sales data that has the SQL schema shown in the following table.
In the Date table, the dateid column has a format of yyyymmdd and the month column has a format
of yyyymm. The week column in the Date table and the weekid column in the Weekly_Returns table
have a format of yyyyww. The regionid column can be managed by only one sales manager.
Data Concerns
You are concerned with the quality and completeness of the sales data.
You plan to verify the sales data for negative sales amounts.
Reporting Requirements
Litware identifies the following technical requirements:
Executives require a visual that shows sales by region.
Regional managers require a visual to analyze weekly sales and returns.
Sales managers must be able to see the sales data of their respective region only.
The sales managers require a visual to analyze sales performance versus sales targets.
The sale department requires reports that contain the number of sales transactions.
Users must be able to see the month in reports as shown in the following example: Feb 2020.
The customer service department requires a visual that can be filtered by both sales month and ship month independently.
QUESTION 1
You need to address the data concerns before creating the data model. What should you do in Power Query Editor?
A. Select Column distribution.
B. Select the sales_amount column and apply a number filter.
C. Select Column profile, and then select the sales_amount column.
D. Transform the sales_amount column to replace negative values with 0.
Answer: C
QUESTION 2
You need to create a calculated column to display the month based on the reporting requirements.
Which DAX expression should you use?
A. FORMAT('Date'[date], "MMM YYYY")
B. FORMAT('Date' [date], "M YY")
C. FORMAT('Date'[date_id], "MMM") & "" & FORMAT('Date'[year], "#")
D. FORMAT('Date' [date_id], "MMM YYYY")
Answer: A
QUESTION 3
You need to create the required relationship for the executive's visual. What should you do before you can create the relationship?
A. Change the data type of Sales[region_id] to Whole Number.
B. In the Sales table, add a measure for sum(sales_amount).
C. Change the data type of sales[sales_id] to Text.
D. Change the data type of sales [region_id] to Decimal Number.
Answer: A
Scenario: Executives require a visual that shows sales by region.
Need to change the sales_id column from Varchar to Whole Number (Integer).
QUESTION 4
What should you create to meet the reporting requirements of the sales department?
A. a measure that uses a formula of SUM (Sales [sales_id])
B. a calculated column that use a formula of COUNTA(sales [sales_id])
C. a measure that uses a formula of COUNTROWS (Sales)
D. a calculated column that uses a formula of SUM (Sales [sales_id])
Answer: C
Explanation:
The sale department requires reports that contain the number of sales transactions.
The COUNTROWS function counts the number of rows in the specified table, or in a table defined by an expression.
QUESTION 5
You need to create a relationship between the Weekly_Returns table and the Date table to meet the
reporting requirements of the regional managers. What should you do?
A. In the Weekly.Returns table, create a new calculated column named date-id in a format of yyyymmdd and use the calculated column to create a relationship to the Date table.
B. Add the Weekly_Returns data to the Sales table by using related DAX functions.
C. Create a new table based on the Date table where date-id is unique, and then create a many-tomany relationship to Weekly_Return.
Answer: A
Explanation:
Scenario: Region managers require a visual to analyze weekly sales and returns.
To relate the two tables we need a common column.
QUESTION 6
HOTSPOT
You need to create a visualization to meet the reporting requirements of the sales managers.
How should you create the visualization? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Scenario: The sales managers require a visual to analyze sales performance versus sales targets.
Box 1: KPI
A Key Performance Indicator (KPI) is a visual cue that communicates the amount of progress made
toward a measurable goal.
Box 2: Sales[sales_amount]
Box 3: Date[month]
Time > FiscalMonth. This value will represent the trend.
Box 4: Targets[sales_target]
QUESTION 7
You need to provide a solution to provide the sales managers with the required access.
What should you include in the solution?
A. Create a security role that has a table filter on the Sales_Manager table where username = UserName()
B. Create a security role that has a table filter on the Region_Manager table where sales_manager_id = UserPrincipalName().
C. Create a security role that has a table filter on the Sales_Manager table where name = UserName().
D. Create a security role that has a table filter on the Sales_Manager table where username = sales_manager_id.
Answer: A
QUESTION 8
You need to create relationships to meet the reporting requirements of the customer service department.
What should you create?
A. an additional date table named ShipDate, a one-to-many relationship from
Sales[sales_date_id] to Date[date_id], and a one-to-many relationship from
Sales[sales_ship_date_id] to ShipDate[date_id]
B. an additional date table named ShipDate, a many-to-many relationship from
Sales[sales_date_id] to Date[date_id], and a many-to-many relationship from
Sales[sales_ship_date_id] to ShipDate[date_id]
C. a one-to-many relationship from Date[date_id] to Sales[sales_date_id] and another one-to-many
relationship from Date[date_id] to Weekly_Returns[week_id]
D. a one-to-many relationship from Sales[sales_date_id] to Date[date_id] and a one-to-many
relationship from Sales[sales_ship_date_id] to Date[date_id]
E. a one-to-many relationship from Date[date_id] to Sales[sales_date_id] and another one-to-many
relationship from Date[date_id] to Sales[sales_ship_date_id]
Answer: A
Explanation:
Scenario: The customer service department requires a visual that can be filtered by both sales month
and ship month independently.
QUESTION 9
HOTSPOT
You publish the dataset to powerbi.com.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
QUESTION 10
You need to get data from the Microsoft SQL Server tables. What should you use to configure the connection'
A. import that uses a Microsoft account
B. DirectQuery that uses the end-user s credentials
C. DirectQuery that uses a database credential
D. Import that uses a database credential
Answer: B
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