Microsoft PL-300 Deutsch real exam prep : 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 23, 2026
  • Q&As: 472 Questions and Answers

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Microsoft PL-300 Deutsch Value Pack (Frequently Bought Together)

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Value Pack Total: $209.97  $89.99

About Microsoft PL-300 Deutsch Real Exam

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The Microsoft Power BI Data Analyst certification is a globally recognized certification that validates your ability to design, build, and optimize data models using Power BI. It also demonstrates your expertise in building queries and reports with appropriate visuals, including dashboards, scorecards, and visualizations. This certification focuses on the intermediate-level skills required for data modeling and analysis.

The Microsoft Power BI Data Analyst certification provides many benefits to you. It helps you boost your career growth by validating your knowledge in building business intelligence solutions using Power BI platform. It validates your skills in designing reports and visualizations for various business needs. It increases your credibility among employers as most companies look for professionals who have this certification. It provides an opportunity to earn a higher salary package compared to those without this certification. Prep4away Microsoft PL-300 Dumps will help you to pass your certification exam and get highly paid job.

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

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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

  • Time Duration: 180 minutes

  • The passing score: 700

  • Number of Questions: 40-60 questions

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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.

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Microsoft PL-300 Deutsch Exam Syllabus Topics:

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

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