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PL-300 Deutsch pdf
  • Exam Code: PL-300 Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Jul 31, 2026
  • Q & A: 515 Questions and Answers
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  • Exam Code: PL-300 Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Jul 31, 2026
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  • Exam Code: PL-300 Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
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Introduction of Microsoft PL-300 Exam

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.

The Microsoft certification exams enable you to validate your knowledge and skills in the system. If you have a job, it helps you to get promoted. The certification is a must-have for IT professionals. Microsoft Power BI Data Analyst Certification Exam is an exam designed by Microsoft for data analysts who are interested in gaining knowledge of the Microsoft Azure cloud platform and Power BI suite tools. The exam tests your ability to design, develop, and implement analytical solutions using Excel, Power Pivot, Power View and other related tools.

What are the steps to follow for the registration of the Microsoft Power BI Data Analyst Certification Exam

The steps to follow for the registration of the Microsoft Power BI Data Analyst Certification Exam are as follows:

  • You will see a list of courses that are available on this website. Select “Microsoft Power BI Data Analyst Certification Exam” and click on “Enroll Now” button.

  • Then you need to select your preferred payment method which includes credit card or PayPal account etc., and you will receive an email confirmation after successful payment using your credit card or PayPal account etc.

  • The next step is to fill out your personal information such as name, email address, country and state city etc., which is mandatory to complete your registration process successfully.

  • Go to the official website of Microsoft, and click on “Microsoft Learning”.

  • After successful registration process, you will receive an email confirmation from Microsoft with all the details about your course including access code etc., which will be sent to your registered email ID provided during registration process.

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Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Russian, Chinese (Traditional), Italian

Retirement date: none

This exam measures your ability to accomplish the following technical tasks: prepare the data; model the data; visualize and analyze the data; and deploy and maintain assets.

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

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

Microsoft PL-300 Deutsch Exam Syllabus Topics:

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

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