Microsoft PL-300 Deutsch : Microsoft Power BI Data Analyst (PL-300 Deutsch Version)

PL-300 Deutsch real exams

Exam Code: PL-300-Deutsch

Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)

Updated: Aug 30, 2026

Q & A: 472 Questions and Answers

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The cost of the Microsoft Power BI Data Analyst Certification Exam is 165 USD.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/pl-300

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Microsoft PL-300 Deutsch Exam Syllabus Topics:

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

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