] PL-300 Deutsch Training Online: Microsoft Power BI Data Analyst (PL-300 Deutsch Version) & Microsoft Power BI Data Analyst (PL-300 Deutsch Version) Dumps Torrent

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

  • Exam Code: PL-300-Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Jul 19, 2026
  • Q & A: 515 Questions and Answers

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About Microsoft PL-300 Deutsch Exam Questions

Skills measured

  • Prepare the data (15-20%)
  • Download the study guide in the preceding “Tip” box for more details about the skills measured on this exam.
  • Visualize and analyze the data (25-30%)
  • Deploy and maintain assets (20-25%)
  • Model the data (30-35%)

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:

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

  • Understanding business context, including organizational strategy and objectives

  • Developing dashboards that provide actionable insights into business performance

  • Creating custom data models that support analysis and reporting requirements

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Microsoft Power BI Data Analyst Exam Certification Details:

Number of Questions40-60
Schedule ExamPearson VUE
Passing Score700 / 1000
Exam CodePL-300
Books / TrainingCourse PL-300T00: Microsoft Power BI Data Analyst
Exam NameMicrosoft Certified - Power BI Data Analyst Associate
Sample QuestionsMicrosoft Power BI Data Analyst Sample Questions
Duration180 mins
Exam Price$165 (USD)

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

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