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

  • Exam Code: PL-300-Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Aug 09, 2026     Q & A: 515 Questions and Answers

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About Microsoft PL-300 Deutsch Exam

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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.

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Passing Score, Duration & Questions For Microsoft PL-300 Exam

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

  • Number of Questions: 40-60 questions

  • The passing score: 700

  • Time Duration: 180 minutes

Prerequisites of Microsoft Power BI Data Analyst Certification Exam

The Microsoft Power BI Data Analyst Certification Exam is a test which assesses your ability to have a high-level understanding of the data analysis process, including collecting, analyzing and visualizing data. It is a certification that will help you gain the required skills to be able to work with business intelligence solutions and tools. To be eligible to take this exam, you must meet the following prerequisites:

  • You have at least one year of experience working with relational databases, such as SQL Server or Oracle. In addition, you should have a basic understanding of how to create queries and reports using SQL Server Management Studio or Toad Data Point.

  • You have at least one year of experience using Power BI Desktop.

  • You are a professional data analyst with 2-4 years of work experience or an IT professional with 2-4 years of experience.

  • You have at least one year of experience using Power Query in Excel, or an equivalent experience using another data analysis tool.

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

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

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Microsoft PL-300 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Prepare the data15-20%- Get data from data sources
  • 1. Identify and connect to data sources
    • 2. Select storage modes
      - Clean, transform, and load data
      • 1. Shape and transform data
        • 2. Clean data using Power Query
          Topic 2: Visualize and analyze data25-35%- Enhance reports for usability
          • 1. Implement drill-through and navigation
            • 2. Apply filters and slicers
              - Create reports and dashboards
              • 1. Design report layouts
                • 2. Create visuals and KPIs
                  Topic 3: Deploy and maintain assets15-20%- Manage workspaces and datasets
                  • 1. Publish and manage datasets
                    • 2. Configure refresh schedules
                      - Secure and monitor Power BI
                      • 1. Monitor usage and performance
                        • 2. Implement row-level security
                          Topic 4: Model the data30-40%- Design a data model
                          • 1. Define relationships and cardinality
                            • 2. Design star schema
                              - Develop a data model
                              • 1. Optimize model performance
                                • 2. Create DAX calculations

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