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Microsoft PL-300 Exam Syllabus Topics:

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

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Microsoft Power BI Data Analyst Sample Questions (Q39-Q44):

NEW QUESTION # 39
Adding an index key and normalizing casing in the data source would help resolve issues with undefined values and errors in a case-sensitive column. The index key can provide a unique identifier, and normalizing casing ensures consistency in the data, which would likely prevent the errors you encountered in the Power BI semantic model.
You have a Power BI data model that imports a date table and a sales table from an Azure SQL database data source. The sales table has the following date foreign keys.
;Due Date
;Order Date
;Delivery Date
You need to support the analysis of sales over time based on all three dates at the same time.
Solution: For each date foreign key, you add inactive relationships between the sales table and the date table.
Does this meet the goal?

Answer: A

Explanation:
The required outcome is to evaluate whether this proposal meets the goal: For each date foreign key, you add inactive relationships between the sales table and the date table. Select B (No). The proposed action - For each date foreign key, you add inactive relationships between the sales table and the date table - does not satisfy the stated goal. Inactive relationships alone do not affect a calculation; they must be activated in a measure, or separate role-playing dimensions must be used when dates need independent simultaneous filters.
Multiple date roles require deliberate relationship design. Active relationships provide the default filter path; inactive relationships can be invoked in a measure, while separate role-playing date dimensions allow simultaneous independent filtering. The current skills outline describes this competency as " Implement role- playing dimensions " .
Microsoft Learn reference: https://learn.microsoft.com/en-us/power-bi/guidance/relationships-active-inactive
| PL-300 objective: " Implement role-playing dimensions " | Study guide: https://learn.microsoft.com/en-us
/credentials/certifications/resources/study-guides/pl-300


NEW QUESTION # 40
You need to create the required relationship for the executive ' s visual. What should you do before you can create the relationship?

Answer: A

Explanation:
The relationship must carry filters from the descriptive table to the transaction table through matching keys.
Bidirectional filtering is reserved for a demonstrated need because it can introduce multiple active paths. The required outcome is to create the required relationship for the executive ' s visual. The supported selection is A (Change the data type of Sales[region_id] to Whole Number). The relevant current PL-300 study-guide bullet is " Define a relationship ' s cardinality and cross-filter direction " . The opposite cardinality or unnecessary bidirectional filtering can duplicate results, block propagation, or create ambiguity rather than solve the stated model path. It also preserves predictable filter context and aggregation behavior when the result is used by several visuals or report pages.
Microsoft Learn reference: https://learn.microsoft.com/en-us/power-bi/transform-model/desktop- relationships-understand | PL-300 objective: " Define a relationship ' s cardinality and cross-filter direction "
| Study guide: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/pl-300


NEW QUESTION # 41
You plan to use Power Query Editor to get data from an API.
The API returns a JSON response.
You have a username and password tor the API.
Which data source and authentication method should you use to connect to the API? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 42
You are profiling data by using Power Query Editor.
You have a table that contains a column named column1. Column statistics and Value distribution for column1 are shown in the following exhibit.

Answer:

Explanation:

Explanation:


NEW QUESTION # 43
You are modifying a Power Bi model by using Power Bl Desktop.
You have a table named Sales that contains the following fields.

You have a table named Transaction Size that contains the following data.

You need to create a calculated column to classify each transaction as small, medium, or large based on the value in Sales Amount.
How should you complete the code? To answer, drag the appropriate values to the correct 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.

Answer:

Explanation:

Explanation:
FILTER | AND | CALCULATE


NEW QUESTION # 44
......

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