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

PL-300 Korean Exam Simulator
  • Exam Code: PL-300-KR
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Korean Version)
  • Updated: Aug 08, 2026
  • Q & A: 515 Questions and Answers
  • Microsoft PL-300 Korean Q&A - in .pdf

  • Printable Microsoft PL-300-KR PDF Format. It is an electronic file format regardless of the operating system platform.
  • PDF Version Price: $69.99
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Prerequisites of Microsoft Power BI Data Analyst Certification Exam

The Microsoft Power BI Data Analyst Certification Exam is a test which assesses your ability to have a high-level understanding of the data analysis process, including collecting, analyzing and visualizing data. It is a certification that will help you gain the required skills to be able to work with business intelligence solutions and tools. To be eligible to take this exam, you must meet the following prerequisites:

  • You have at least one year of experience working with relational databases, such as SQL Server or Oracle. In addition, you should have a basic understanding of how to create queries and reports using SQL Server Management Studio or Toad Data Point.

  • You are a professional data analyst with 2-4 years of work experience or an IT professional with 2-4 years of experience.

  • You have at least one year of experience using Power BI Desktop.

  • You have at least one year of experience using Power Query in Excel, or an equivalent experience using another data analysis tool.

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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Microsoft PL-300 Korean exam simulator

Microsoft PL-300 Korean 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. Create dashboards and pinned elements
          • 2. Design report layout, formatting, and interactivity
            • 3. Apply filters, slicers, and drill-through
              • 4. Choose appropriate visualizations
                - Perform data analysis
                • 1. Interpret results and identify trends
                  • 2. Implement custom visuals and R/Python scripts
                    • 3. Create and manage bookmarks and tooltips
                      Topic 2: Manage and secure Power BI15-20%- Manage workspaces and assets
                      • 1. Create and configure workspaces
                        • 2. Publish, update, and organize reports/datasets
                          • 3. Manage data refresh and scheduled updates
                            - Deploy and distribute content
                            • 1. Embed content in applications or websites
                              • 2. Share reports, dashboards, and apps
                                • 3. Monitor usage and performance
                                  - 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
                                        Topic 3: Prepare the data25-30%- 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
                                                - Get or connect to data
                                                • 1. Identify and connect to data sources or shared semantic models
                                                  • 2. Create and modify parameters
                                                    • 3. Configure data source settings, credentials, and privacy levels
                                                      • 4. Choose storage modes: Import, DirectQuery, DirectLake
                                                        - Load and configure data
                                                        • 1. Configure data refresh settings
                                                          • 2. Integrate data from multiple sources
                                                            • 3. Define table structures and properties
                                                              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
                                                                    - Design data models
                                                                    • 1. Create common date tables
                                                                      • 2. Create relationships: cardinality, cross-filter direction, security
                                                                        • 3. Implement role-playing dimensions
                                                                          • 4. Define tables, columns, and hierarchies
                                                                            - Optimize model performance
                                                                            • 1. Optimize relationships and calculations
                                                                              • 2. Use aggregations and composite models
                                                                                • 3. Reduce cardinality and data size

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