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

PL-300 Deutsch actual test
  • Exam Code: PL-300-Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Aug 06, 2026
  • Q & A: 515 Questions and Answers
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About Microsoft Power BI Data Analyst (PL-300 Deutsch Version) : PL-300 Deutsch Exam

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There are many IT certifications available in the market today, but if you are looking for a job as a data analyst then you should give this certification a chance. This certification will help you to stand out from the crowd and get hired easily by many companies. Microsoft Power BI Data Analyst Certification Exam is the most valuable certification program for IT professionals in their respective fields. Microsoft PL-300 Dumps is a must-have certificate for all IT professionals who want to pursue their career in the field of data analytics.

The Microsoft Power BI Data Analyst Certification Exam is a certification exam that will help you to demonstrate your expertise in using the Microsoft Power BI platform. This exam tests the candidate's ability to analyze data with Power BI and create reports that are accurate, insightful and easy to read. Once you pass this exam, you will receive a certificate that shows your competence in performing these tasks. The certificate is valid for three years, so if you want to keep your skills up-to-date then you should take additional training during this time period.

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

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