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

PL-300 Korean testking pdf

Exam Code: PL-300-KR

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

Updated: Aug 29, 2026

Q & A: 472 Questions and Answers

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The Importance Of Microsoft Power BI Data Analyst Certification Exam For A Career In IT

The world of IT is changing rapidly. The demand for skilled professionals has reached its peak. With the increase in number of software companies, the competition has also increased. There are a lot of opportunities for professionals with high level skills. One such skill is Microsoft Power BI Data Analyst Certification Exam. This exam is designed to test your knowledge on data analysis concepts and also on different tools that you can use to solve problems related to data analysis.

There are many ways to get certified as a data analyst or BI professional. You can go through a formal education program or attend classes offered by various institutions and organizations. However, if you want to ensure that you get the best job opportunities and get hired easily, then getting certified is what you need to do. Here at TestkingPDF our Microsoft PL-300 Dumps will help you to get certified. Basic measures of column chart scenario have scenario based questions that shared dataset of calculated table.

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Passing Score, Duration & Questions For Microsoft PL-300 Exam

  • Time Duration: 180 minutes

  • The passing score: 700

  • Number of Questions: 40-60 questions

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

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

Why Microsoft Power BI Data Analyst Certification Exam is so difficult

No matter how many times you take the Microsoft Power BI Data Analyst Certification Exam, you will never be able to finish it. This is because the exam is designed to be as difficult as possible. When you first sit down and begin answering questions, you may feel like there are a lot of easy ones. This is just part of the test's strategy. they want to make sure that you think everything's going smoothly, so that when they throw in a difficult question later on, it will be much harder for you to answer.

The Microsoft certification exams are considered to be the toughest in the industry. This is because of the fact that if you have passed one of these exams, then it means that you have gone through a tough time and have shown that you are capable enough to handle any situation. Microsoft Power BI Data Analyst Certification Exam is designed to give you a hard time. It won't let up until you finally give up entirely and surrender your certification. TestkingPDF Microsoft PL-300 Dumps are the only way to pass your exam and get certified in your first attempt.

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:

  • Understanding business context, including organizational strategy and objectives

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

  • Developing dashboards that provide actionable insights into business performance

  • Creating custom data models that support analysis and reporting requirements

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Microsoft PL-300 Korean Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Visualize and analyze data25-30%- Create reports and dashboards
  • 1. Create dashboards and pinned elements
    • 2. Choose appropriate visualizations
      • 3. Apply filters, slicers, and drill-through
        • 4. Design report layout, formatting, and interactivity
          - Enhance reports with analytics
          • 1. Create paginated reports
            • 2. Use AI visuals, forecasts, and key influencers
              • 3. Apply conditional formatting and custom visuals
                - Perform data analysis
                • 1. Interpret results and identify trends
                  • 2. Create and manage bookmarks and tooltips
                    • 3. Implement custom visuals and R/Python scripts
                      Topic 2: Prepare the data25-30%- Profile and clean data
                      • 1. Transform data using Power Query Editor
                        • 2. Resolve inconsistencies, null values, and errors
                          • 3. Manage data types, columns, and rows
                            • 4. Evaluate data statistics and column properties
                              - 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
                                      - Load and configure data
                                      • 1. Integrate data from multiple sources
                                        • 2. Configure data refresh settings
                                          • 3. Define table structures and properties
                                            Topic 3: Manage and secure Power BI15-20%- Manage workspaces and assets
                                            • 1. Manage data refresh and scheduled updates
                                              • 2. Publish, update, and organize reports/datasets
                                                • 3. Create and configure workspaces
                                                  - Implement security and governance
                                                  • 1. Manage permissions and access
                                                    • 2. Configure row-level security (RLS) and object-level security
                                                      • 3. Apply data sensitivity labels and protection
                                                        - 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. Optimize relationships and calculations
                                                                  • 3. Use aggregations and composite models
                                                                    - Design data models
                                                                    • 1. Create relationships: cardinality, cross-filter direction, security
                                                                      • 2. Implement role-playing dimensions
                                                                        • 3. Define tables, columns, and hierarchies
                                                                          • 4. Create common date tables
                                                                            - Create model calculations
                                                                            • 1. Use DAX: calculated columns, calculated tables, measures
                                                                              • 2. Use CALCULATE and filter context
                                                                                • 3. Implement aggregation and time intelligence

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