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

PL-300 Deutsch

Exam Code: PL-300-Deutsch

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

Updated: Aug 25, 2026

Q & A: 472 Questions and Answers

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

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Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Russian, Chinese (Traditional), Italian

Retirement date: none

This exam measures your ability to accomplish the following technical tasks: prepare the data; model the data; visualize and analyze the data; and deploy and maintain assets.

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

Learn more about the exam

The need for this exam has increased tremendously over the years. As more people start using technology, there is a greater need for more professionals who can help them with their problems. With the increasing demand for people with these skills, it will be difficult for you to get a job without having one. If you want to succeed in your career, you should consider taking this test because it will give you an edge over other candidates who do not have it. It will also help you stand out from the crowd if you are applying for jobs online or even if you are looking for promotion within your company. Column data types have questions and answers subcategories for real time scenario. Sample questions about data source settings have calculated columns mobile view. Quick measure mode filters the app syllabus to practice the average sales. If you are feeling sensitive to additives in your food, you may want to format your schema prepared environment to be more additive-sensitive. This could involve avoiding foods that contain additives, eating organic foods whenever possible, or using natural sweeteners.

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What is the salary of the Microsoft Power BI Data Analyst Certified professional

The Average salary of different countries of Microsoft Power BI Data Analyst certified professionals:

  • India; INR 500,000

  • United States; USD 90,000

  • Australia; AUD 75,000

  • United Kingdom; POUNDS 60,000

  • Canada; CAD 70,000

Solutions

Microsoft Power BI Data Analyst Certification Exam is one of the most popular certification exams in the market. However, most candidates don't pass it on their first attempt. The reasons for this are many, but the most common ones are not having enough time to prepare, not knowing where to start and what to study, or not having access to quality learning materials. To help you overcome these obstacles and pass Microsoft Power BI Data Analyst Certification Exam easily, our experts have created a comprehensive Microsoft PL-300 Dumps that will give you everything you need to know to pass Microsoft Power BI Data Analyst Certification Exam quickly and efficiently.

This study guide contains everything you will need to have a deep understanding of this certification and take it with confidence. Our experts have taken great care in creating this study guide by using only high-quality resources available on the internet. Our goal is to help you understand each concept so that when taking the exam, there will be no surprises that throw off your momentum or cause you any stress during your preparation or while taking the exam itself.

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. 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
                    Topic 2: Prepare the data25-30%- Load and configure data
                    • 1. Define table structures and properties
                      • 2. Integrate data from multiple sources
                        • 3. Configure data refresh settings
                          - Profile and clean data
                          • 1. Transform data using Power Query Editor
                            • 2. Manage data types, columns, and rows
                              • 3. Evaluate data statistics and column properties
                                • 4. Resolve inconsistencies, null values, and errors
                                  - 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
                                          Topic 3: 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. Choose appropriate visualizations
                                                  • 2. Apply filters, slicers, and drill-through
                                                    • 3. Design report layout, formatting, and interactivity
                                                      • 4. Create dashboards and pinned elements
                                                        - Perform data analysis
                                                        • 1. Implement custom visuals and R/Python scripts
                                                          • 2. Interpret results and identify trends
                                                            • 3. Create and manage bookmarks and tooltips
                                                              Topic 4: Model the data25-30%- Create model calculations
                                                              • 1. Use CALCULATE and filter context
                                                                • 2. Use DAX: calculated columns, calculated tables, measures
                                                                  • 3. Implement aggregation and time intelligence
                                                                    - Optimize model performance
                                                                    • 1. Optimize relationships and calculations
                                                                      • 2. Reduce cardinality and data size
                                                                        • 3. Use aggregations and composite models
                                                                          - Design data models
                                                                          • 1. Create relationships: cardinality, cross-filter direction, security
                                                                            • 2. Define tables, columns, and hierarchies
                                                                              • 3. Create common date tables
                                                                                • 4. Implement role-playing dimensions

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