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

PL-300 Deutsch real exams

Exam Code: PL-300-Deutsch

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

Updated: Jul 23, 2026

Q & A: 515 Questions and Answers

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What are the special features of the Microsoft Power BI Data Analyst Certification Exam

The Microsoft Power BI Data Analyst Certification Exam will help you prepare for the new job role of a data analyst. A certified Data Analyst can use this exam to prove their skills in using Power BI to analyze business data, generate insightful visualizations, and share them with customers. Microsoft PL-300 Dumps is designed to test your knowledge of business data modeling, data analysis and visualization, and dashboard development in Power BI. The exam will cover the following topics:

  • Developing dashboards that provide actionable insights into business performance

  • Identifying sources of data that can contribute to achieving business goals

  • Understanding business context, including organizational strategy and objectives

  • Creating custom data models that support analysis and reporting requirements

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

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Introduction of Microsoft PL-300 Exam

Microsoft offers a wide range of certifications to enhance your knowledge in various areas of IT. The Microsoft Power BI Data Analyst Certification Exam is one of the most popular and sought-after Microsoft certification exams which aims to develop your skills as a data analyst by providing you with an opportunity to learn about basic business intelligence concepts, data analysis techniques and tools that can be used for building data models. Microsoft PL-300 Dumps are the best way to pass your exam.

The Microsoft certification exams enable you to validate your knowledge and skills in the system. If you have a job, it helps you to get promoted. The certification is a must-have for IT professionals. Microsoft Power BI Data Analyst Certification Exam is an exam designed by Microsoft for data analysts who are interested in gaining knowledge of the Microsoft Azure cloud platform and Power BI suite tools. The exam tests your ability to design, develop, and implement analytical solutions using Excel, Power Pivot, Power View and other related tools.

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Microsoft PL-300 Deutsch Exam Syllabus Topics:

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

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