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

PL-300 Deutsch testking pdf

Exam Code: PL-300-Deutsch

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

Updated: Aug 19, 2026

Q & A: 472 Questions and Answers

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Exam PL-300: Microsoft Power BI Data Analyst

The Power BI data analyst delivers actionable insights by leveraging available data and applying domain expertise. The Power BI data analyst collaborates with key stakeholders across verticals to identify business requirements, cleans and transforms the data, and then designs and builds data models by using Power BI. The Power BI data analyst provides meaningful business value through easy-to-comprehend data visualizations, enables others to perform self-service analytics, and deploys and configures solutions for consumption. Candidates for this exam should be proficient using Power Query and writing expressions by using DAX.

Passing score: 700. Learn more about exam scores.

Part of the requirements for: Microsoft Certified: Power BI Data Analyst Associate

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

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Microsoft PL-300 Deutsch Exam Syllabus Topics:

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

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