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

Microsoft PL-300 Deutsch test insides dumps
  • Exam Code: PL-300-Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Sep 01, 2026
  • Q & A: 472 Questions and Answers
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Microsoft Power BI Data Analyst Certification Exam Reference

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

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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

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Microsoft PL-300 Deutsch Exam Syllabus Topics:
SectionWeightObjectives
Topic 1: Prepare the data25-30%- 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. Evaluate data statistics and column properties
              • 3. Resolve inconsistencies, null values, and errors
                • 4. Transform data using Power Query Editor
                  - Load and configure data
                  • 1. Integrate data from multiple sources
                    • 2. Define table structures and properties
                      • 3. Configure data refresh settings
                        Topic 2: Model the data25-30%- Optimize model performance
                        • 1. Use aggregations and composite models
                          • 2. Reduce cardinality and data size
                            • 3. Optimize relationships and calculations
                              - Design data models
                              • 1. Create relationships: cardinality, cross-filter direction, security
                                • 2. Implement role-playing dimensions
                                  • 3. Define tables, columns, and hierarchies
                                    • 4. Create common date tables
                                      - Create model calculations
                                      • 1. Implement aggregation and time intelligence
                                        • 2. Use DAX: calculated columns, calculated tables, measures
                                          • 3. Use CALCULATE and filter context
                                            Topic 3: Visualize and analyze data25-30%- Create reports and dashboards
                                            • 1. Create dashboards and pinned elements
                                              • 2. Apply filters, slicers, and drill-through
                                                • 3. Choose appropriate visualizations
                                                  • 4. Design report layout, formatting, and interactivity
                                                    - Perform data analysis
                                                    • 1. Implement custom visuals and R/Python scripts
                                                      • 2. Interpret results and identify trends
                                                        • 3. Create and manage bookmarks and tooltips
                                                          - Enhance reports with analytics
                                                          • 1. Create paginated reports
                                                            • 2. Use AI visuals, forecasts, and key influencers
                                                              • 3. Apply conditional formatting and custom visuals
                                                                Topic 4: Manage and secure Power BI15-20%- Implement security and governance
                                                                • 1. Manage permissions and access
                                                                  • 2. Configure row-level security (RLS) and object-level security
                                                                    • 3. Apply data sensitivity labels and protection
                                                                      - 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. Embed content in applications or websites
                                                                                • 3. Share reports, dashboards, and apps

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