Microsoft PL-300 Study Test & Valid PL-300 Test Practice

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Microsoft PL-300 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Visualize the Data25-30%- Build visuals
  • 1. Determine the appropriate visual type
  • 2. Configure visual interactions and cross-filtering
  • 3. Format and configure pages and report backgrounds
  • 4. Apply sorting and filtering to visuals
  • 5. Apply AI insights and enhanced analytics
  • 6. Configure data colors and shapes
- Enhance reports for user experience
  • 1. Apply artistic formatting to visuals
  • 2. Add accessibility features and compliance
  • 3. Add tooltips and navigation
  • 4. Design for mobile and specific layouts
- Enrich reports with advanced visuals
  • 1. Use dynamic page navigation
  • 2. Configure R and Python visuals
  • 3. Create custom visuals
  • 4. Integrate Microsoft Copilot for Power BI
Topic 2: Model the Data25-30%- Develop the data model
  • 1. Build hierarchies and hierarchical fields
  • 2. Create common date tables
  • 3. Create calculated tables and columns
  • 4. Configure table relationships
  • 5. Use the calculation group feature
  • 6. Implement row-level security roles
- Optimize model performance
  • 1. Configure aggregations
  • 2. Validate performance and resolve issues
  • 3. Improve user experience by hiding objects
  • 4. Optimize Dax queries
  • 5. Optimize DirectQuery models
- Create measures and DAX calculations
  • 1. Create calculated measures
  • 2. Implement context transition
  • 3. Use Time Intelligence functions
  • 4. Use CALCULATE and FILTER functions
  • 5. Write and use basic DAX syntax
  • 6. Create semi-additive measures
- Design a data model
  • 1. Define tables and table schemas
  • 2. Apply field metadata and groupings
  • 3. Determine the appropriate granularity
  • 4. Design a star schema or snowflake schema
  • 5. Implement row-level security
  • 6. Resolve performance issues with relationships
Topic 3: Analyze the Data10-15%- Work with metrics in Power BI
  • 1. Create metrics using Microsoft measurements
  • 2. Track goals with scorecards
  • 3. Define and monitor KPIs
  • 4. Use the Decomposition Tree visual
- Perform analysis in Power BI
  • 1. Identify patterns and trends
  • 2. Generate Pinn visual insights
  • 3. Use the Q&A visual
  • 4. Configure auto-insights
  • 5. Apply Quick Insights
Topic 4: Prepare the Data10-15%- Clean, transform, and load the data
  • 1. Design and build intermediate tables
  • 2. Configure data loading and queries
  • 3. Identify the data structure
  • 4. Profile the data
  • 5. Determine proper data types
  • 6. Apply user-friendly naming conventions to columns and tables
  • 7. Resolve data quality issues
- Get data from various data sources
  • 1. Choose between DirectQuery, Import, and Dual storage modes
  • 2. Use Microsoft Fabric and OneLake
  • 3. Change data source settings
  • 4. Configure dataset refresh
  • 5. Identify and connect to a data source
  • 6. Select a shared dataset or create a local copy
Topic 5: Manage and Maintain Workspace Items10-15%- Manage datasets
  • 1. Configure dataset metadata and properties
  • 2. Resolve dataset permission issues
  • 3. Manage gateways and data sources
  • 4. Manage dataset refresh scheduling
- Create and manage workspaces
  • 1. Configure content certification
  • 2. Configure workspace membership and roles
  • 3. Endorse sensitive content with sensitivity labels
  • 4. Publish and update a Power BI app

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Microsoft Power BI Data Analyst Sample Questions (Q22-Q27):

NEW QUESTION # 22
You have two CSV files named Products and Categories.
The Products file contains the following columns:
* ProductID
* ProductName
* SupplierID
* CategoryID
The Categories file contains the following columns:
* CategoryID
* CategoryName
* CategoryDescription
From Power BI Desktop, you import the files into Power Query Editor.
You need to create a Power BI dataset that will contain a single table named Product. The Product will table includes the following columns:
* ProductID
* ProductName
* SupplierID
* CategoryID
* CategoryName
* CategoryDescription
How should you combine the queries, and what should you do on the Categories query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
Answer as selected


NEW QUESTION # 23
You plan to create the chart shown in the following exhibit.

How should you create the dashed horizontal line denoting the 40th percentile of daily sales for the period shown?

Answer: A

Explanation:
The analytics feature enables you to show percentiles across groups specified along a specific axis.
Example:
1. Click on the analytics tab
2. Select Percentile
3. You can choose a specific percentile along with other formatting options.
4. Drag a date or non-numeric dimension into the Axis of a column chart


Add percentile lines to monitor daily revenue


NEW QUESTION # 24
You have two tables named Customers and Invoice in a Power BI model. The Customers table contains the following fields:
CustomerID
Customer City
Customer State
Customer Name
Customer Address 1
Customer Address 2
Customer Postal Code
The Invoice table contains the following fields:
Order ID
Invoice ID
Invoice Date
Customer ID
Total Amount
Total Item Count
The Customers table is related to the Invoice table through the Customer ID columns. A customer can have many invoices within one month.
The Power BI model must provide the following information:
The number of customers invoiced in each state last month
The average invoice amount per customer in each postal code
You need to define the relationship from the Customers table to the Invoice table. The solution must optimize query performance.
What should you configure? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/power-bi/transform-model/desktop-relationships-understand


NEW QUESTION # 25
You are designing the data model for a Power Bl semantic model. You have the following tables in the star schema.

Which table is the fact table of the star schema, and which column in the Patient table is the surrogate key of the star schema? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 26
You have the CSV file shown in the following table.

You use Power Query Editor to preview the data in the file.
You need to transform the data to meet the following requirements:
; The first column must contain the month.
; The second column must contain the year.
; The third column must contain the order amount for the month and year.
Which transformation should you use first?

Answer: A

Explanation:
The supported selection is A (unpivot). The key constraint is to transform the data to meet the following requirements:; The first column must contain the month.; The second column must contain the year.; The third column must contain. Pivoting makes a table wider, while unpivoting converts repeated period or category columns into attribute-value rows that visuals can aggregate consistently. Unpivot converts repeated columns into Attribute and Value rows while preserving the identifier columns. This normalizes a wide source so one measure column can be filtered, grouped, and charted consistently. In Microsoft ' s current exam outline, the corresponding objective is " Pivot, unpivot, and transpose data " .
Microsoft Learn reference: https://learn.microsoft.com/en-us/power-query/unpivot-column | PL-300 objective: " Pivot, unpivot, and transpose data " | Study guide: https://learn.microsoft.com/en-us/credentials
/certifications/resources/study-guides/pl-300


NEW QUESTION # 27
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