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


"Microsoft Power BI Data Analyst (PL-300 Korean Version)", also known as PL-300 exam, is a Microsoft Certification. With the complete collection of questions and answers, ExamcollectionPass has assembled to take you through 472 Q&As to your PL-300 Exam preparation. In the PL-300 exam resources, you will cover every field and category in Microsoft Certified: Power BI Data Analyst Associate Certification helping to ready you for your successful Microsoft Certification.

  • Exam Code: PL-300
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Korean Version)
  • Total Questions: 472

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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:

  • 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

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

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Skills measured

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

Microsoft PL-300 Korean Exam Syllabus Topics:

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

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