2026 Valid PL-300: Microsoft Power BI Data Analyst Reliable Test Braindumps

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Microsoft PL-300 Exam Syllabus Topics:

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

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Microsoft Power BI Data Analyst Sample Questions (Q376-Q381):

NEW QUESTION # 376
Drag and Drop Question
You use Power Query Editor to load two queries named Query1 and Query2.
Query1 results in the following error.

Query2 results in the following error.

Which type of error occurred for each query? To answer, drag the appropriate error types to the correct queries. Each error type 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:
Step-level Error: a step-level error prevents the query from loading and displays the error components in a yellow pane Cell-level Error: a cell-level error won't prevent the query from loading but displays error values as Error in the cell.


NEW QUESTION # 377
You have an app workspace that contains a dashboard and four reports. All the reports are generated from a single dataset that contains sales data for your company.
The reports display the data configured as shown in the following table.

You need to ensure that the users of the reports can locate the correct report by using natural language queries.
What should you do?

Answer: C

Explanation:
References: https://docs.microsoft.com/en-us/power-bi/service-q-and-a-direct-query#limitations-during- public-preview


NEW QUESTION # 378
You are creating a Microsoft Power Bl model that has two tables named CityData and Sales. CityData contains only the data shown in the following table.

Sales contains only the data shown in the following table.

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:

Reference:
https://docs.microsoft.com/en-us/dax/related-function-dax
https://docs.microsoft.com/en-us/dax/calculate-function-dax


NEW QUESTION # 379
You have a query that returns the data shown in the following exhibit.

You need to configure the query to display the data as shown in the following exhibit.

Which step should you use in the query?

Answer: A

Explanation:
Power Query Unpivot columns: 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.

Note:
Syntax: Table.Unpivot(table as table, pivotColum ns as list, attributeColumn as text, valueColumn as text) as table Table.Unpivot translates a set of columns in a table into attribute-value pairs, combined with the rest of the values in each row.
Reference:
https://docs.microsoft.com/en-us/power-query/ unpivot-column
https://docs.microsoft.com/en-us/powerquery-m/table-unpivot


NEW QUESTION # 380
You import a Power Bl dataset that contains the following tables:
* Date
* Product
* Product Inventory
The Product inventory table contains 25 million rows. A sample of the data is shown in the following table.

The Product Inventory table relates to the Date table by using the DateKey column. The Product inventory table relates to the Product table by using the ProductKey column. You need to reduce the size of the data model without losing information. What should you do?

Answer: B


NEW QUESTION # 381
......

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