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Microsoft PL-300 Deutsch

PL-300 Deutsch

Exam Code: PL-300-Deutsch

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

Updated: Aug 20, 2026

Q&A Number: 472 Q&As

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About Microsoft PL-300 Deutsch Exam Questions and Answers

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

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.

Is Microsoft Power BI Data Analyst Certification Exam Worth It

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.

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Microsoft PL-300 Deutsch Exam Syllabus Topics:

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

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