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

PL-300 Deutsch

Exam Code: PL-300-Deutsch

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

Updated: Aug 28, 2026

Q & A: 472 Questions and Answers

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

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Learn more about the exam

The need for this exam has increased tremendously over the years. As more people start using technology, there is a greater need for more professionals who can help them with their problems. With the increasing demand for people with these skills, it will be difficult for you to get a job without having one. If you want to succeed in your career, you should consider taking this test because it will give you an edge over other candidates who do not have it. It will also help you stand out from the crowd if you are applying for jobs online or even if you are looking for promotion within your company. Column data types have questions and answers subcategories for real time scenario. Sample questions about data source settings have calculated columns mobile view. Quick measure mode filters the app syllabus to practice the average sales. If you are feeling sensitive to additives in your food, you may want to format your schema prepared environment to be more additive-sensitive. This could involve avoiding foods that contain additives, eating organic foods whenever possible, or using natural sweeteners.

Microsoft PL-300 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Model the Data25-30%- Optimize model performance
  • 1. Optimize DirectQuery models
  • 2. Configure aggregations
  • 3. Optimize Dax queries
  • 4. Validate performance and resolve issues
  • 5. Improve user experience by hiding objects
- Create measures and DAX calculations
  • 1. Use CALCULATE and FILTER functions
  • 2. Use Time Intelligence functions
  • 3. Create semi-additive measures
  • 4. Implement context transition
  • 5. Write and use basic DAX syntax
  • 6. Create calculated measures
- Develop the data model
  • 1. Use the calculation group feature
  • 2. Configure table relationships
  • 3. Build hierarchies and hierarchical fields
  • 4. Implement row-level security roles
  • 5. Create common date tables
  • 6. Create calculated tables and columns
- Design a data model
  • 1. Define tables and table schemas
  • 2. Implement row-level security
  • 3. Resolve performance issues with relationships
  • 4. Design a star schema or snowflake schema
  • 5. Apply field metadata and groupings
  • 6. Determine the appropriate granularity
Visualize the Data25-30%- Build visuals
  • 1. Format and configure pages and report backgrounds
  • 2. Apply sorting and filtering to visuals
  • 3. Configure visual interactions and cross-filtering
  • 4. Apply AI insights and enhanced analytics
  • 5. Configure data colors and shapes
  • 6. Determine the appropriate visual type
- Enhance reports for user experience
  • 1. Design for mobile and specific layouts
  • 2. Add accessibility features and compliance
  • 3. Apply artistic formatting to visuals
  • 4. Add tooltips and navigation
- 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
Manage and Maintain Workspace Items10-15%- Manage datasets
  • 1. Configure dataset metadata and properties
  • 2. Manage dataset refresh scheduling
  • 3. Manage gateways and data sources
  • 4. Resolve dataset permission issues
- Create and manage workspaces
  • 1. Configure workspace membership and roles
  • 2. Publish and update a Power BI app
  • 3. Configure content certification
  • 4. Endorse sensitive content with sensitivity labels
Prepare the Data10-15%- Get data from various data sources
  • 1. Select a shared dataset or create a local copy
  • 2. Identify and connect to a data source
  • 3. Configure dataset refresh
  • 4. Choose between DirectQuery, Import, and Dual storage modes
  • 5. Change data source settings
  • 6. Use Microsoft Fabric and OneLake
- Clean, transform, and load the data
  • 1. Determine proper data types
  • 2. Apply user-friendly naming conventions to columns and tables
  • 3. Profile the data
  • 4. Identify the data structure
  • 5. Configure data loading and queries
  • 6. Resolve data quality issues
  • 7. Design and build intermediate tables
Analyze the Data10-15%- Perform analysis in Power BI
  • 1. Use the Q&A visual
  • 2. Configure auto-insights
  • 3. Apply Quick Insights
  • 4. Identify patterns and trends
  • 5. Generate Pinn visual insights
- Work with metrics in Power BI
  • 1. Track goals with scorecards
  • 2. Define and monitor KPIs
  • 3. Create metrics using Microsoft measurements
  • 4. Use the Decomposition Tree visual
PL-300-Deutsch Related Exams
PL-300-KR - Microsoft Power BI Data Analyst (PL-300 Korean Version)
PL-300 - Microsoft Power BI Data Analyst
PL-300J - Microsoft Power BI Data Analyst (PL-300日本語版)
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