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

PL-300 Deutsch real exams

Exam Code: PL-300-Deutsch

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

Updated: Aug 08, 2026

Q & A: 515 Questions and Answers

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

  • Time Duration: 180 minutes

  • 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

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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:

  • 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.

  • 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.

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

  • 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.

  • 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.

Schedule exam

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

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The Importance Of Microsoft Power BI Data Analyst Certification Exam For A Career In IT

The world of IT is changing rapidly. The demand for skilled professionals has reached its peak. With the increase in number of software companies, the competition has also increased. There are a lot of opportunities for professionals with high level skills. One such skill is Microsoft Power BI Data Analyst Certification Exam. This exam is designed to test your knowledge on data analysis concepts and also on different tools that you can use to solve problems related to data analysis.

There are many ways to get certified as a data analyst or BI professional. You can go through a formal education program or attend classes offered by various institutions and organizations. However, if you want to ensure that you get the best job opportunities and get hired easily, then getting certified is what you need to do. Here at PassTorrent our Microsoft PL-300 Dumps will help you to get certified. Basic measures of column chart scenario have scenario based questions that shared dataset of calculated table.

Microsoft PL-300 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Manage and secure Power BI15-20%- Manage workspaces and assets
  • 1. Create and configure workspaces
    • 2. Manage data refresh and scheduled updates
      • 3. Publish, update, and organize reports/datasets
        - Implement security and governance
        • 1. Apply data sensitivity labels and protection
          • 2. Manage permissions and access
            • 3. Configure row-level security (RLS) and object-level security
              - Deploy and distribute content
              • 1. Share reports, dashboards, and apps
                • 2. Embed content in applications or websites
                  • 3. Monitor usage and performance
                    Topic 2: Prepare the data25-30%- Get or connect to data
                    • 1. Identify and connect to data sources or shared semantic models
                      • 2. Create and modify parameters
                        • 3. Choose storage modes: Import, DirectQuery, DirectLake
                          • 4. Configure data source settings, credentials, and privacy levels
                            - Profile and clean data
                            • 1. Transform data using Power Query Editor
                              • 2. Manage data types, columns, and rows
                                • 3. Resolve inconsistencies, null values, and errors
                                  • 4. Evaluate data statistics and column properties
                                    - Load and configure data
                                    • 1. Integrate data from multiple sources
                                      • 2. Define table structures and properties
                                        • 3. Configure data refresh settings
                                          Topic 3: Model the data25-30%- Design data models
                                          • 1. Create relationships: cardinality, cross-filter direction, security
                                            • 2. Create common date tables
                                              • 3. Implement role-playing dimensions
                                                • 4. Define tables, columns, and hierarchies
                                                  - Create model calculations
                                                  • 1. Use DAX: calculated columns, calculated tables, measures
                                                    • 2. Implement aggregation and time intelligence
                                                      • 3. Use CALCULATE and filter context
                                                        - Optimize model performance
                                                        • 1. Optimize relationships and calculations
                                                          • 2. Use aggregations and composite models
                                                            • 3. Reduce cardinality and data size
                                                              Topic 4: Visualize and analyze data25-30%- Create reports and dashboards
                                                              • 1. Apply filters, slicers, and drill-through
                                                                • 2. Design report layout, formatting, and interactivity
                                                                  • 3. Choose appropriate visualizations
                                                                    • 4. Create dashboards and pinned elements
                                                                      - Perform data analysis
                                                                      • 1. Create and manage bookmarks and tooltips
                                                                        • 2. Implement custom visuals and R/Python scripts
                                                                          • 3. Interpret results and identify trends
                                                                            - Enhance reports with analytics
                                                                            • 1. Apply conditional formatting and custom visuals
                                                                              • 2. Create paginated reports
                                                                                • 3. Use AI visuals, forecasts, and key influencers

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