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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: Jul 29, 2026

Q & A: 515 Questions and Answers

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The Microsoft Power BI Data Analyst Certification Exam will help you prepare for the new job role of a data analyst. A certified Data Analyst can use this exam to prove their skills in using Power BI to analyze business data, generate insightful visualizations, and share them with customers. Microsoft PL-300 Dumps is designed to test your knowledge of business data modeling, data analysis and visualization, and dashboard development in Power BI. The exam will cover the following topics:

  • Identifying sources of data that can contribute to achieving business goals

  • Creating custom data models that support analysis and reporting requirements

  • Developing dashboards that provide actionable insights into business performance

  • Understanding business context, including organizational strategy and objectives

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Skills measured

  • Deploy and maintain assets (20-25%)
  • Visualize and analyze the data (25-30%)
  • Prepare the data (15-20%)
  • Model the data (30-35%)
  • Download the study guide in the preceding “Tip” box for more details about the skills measured on this exam.

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

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Microsoft offers a wide range of certifications to enhance your knowledge in various areas of IT. The Microsoft Power BI Data Analyst Certification Exam is one of the most popular and sought-after Microsoft certification exams which aims to develop your skills as a data analyst by providing you with an opportunity to learn about basic business intelligence concepts, data analysis techniques and tools that can be used for building data models. Microsoft PL-300 Dumps are the best way to pass your exam.

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Microsoft PL-300 Deutsch Exam Syllabus Topics:

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