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Microsoft PL-300 Korean

PL-300 Korean

Exam Code: PL-300-KR

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

Updated: Oct 15, 2026

Q&A Number: 472 Q&As

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About Microsoft PL-300 Korean Exam Questions and Answers

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

  • Time Duration: 180 minutes

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

  • Number of Questions: 40-60 questions

  • The passing score: 700

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PL-300 Korean Online Test Engine

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What are the steps to follow for the registration of the Microsoft Power BI Data Analyst Certification Exam

The steps to follow for the registration of the Microsoft Power BI Data Analyst Certification Exam are as follows:

  • Then you need to select your preferred payment method which includes credit card or PayPal account etc., and you will receive an email confirmation after successful payment using your credit card or PayPal account etc.

  • Go to the official website of Microsoft, and click on “Microsoft Learning”.

  • You will see a list of courses that are available on this website. Select “Microsoft Power BI Data Analyst Certification Exam” and click on “Enroll Now” button.

  • After successful registration process, you will receive an email confirmation from Microsoft with all the details about your course including access code etc., which will be sent to your registered email ID provided during registration process.

  • The next step is to fill out your personal information such as name, email address, country and state city etc., which is mandatory to complete your registration process successfully.

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

Microsoft PL-300 Korean Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Prepare the data25-30%- 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. Resolve inconsistencies, null values, and errors
              • 4. Manage data types, columns, and rows
                - 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
                        Topic 2: Manage and secure Power BI15-20%- Implement security and governance
                        • 1. Configure row-level security (RLS) and object-level security
                          • 2. Apply data sensitivity labels and protection
                            • 3. Manage permissions and access
                              - Deploy and distribute content
                              • 1. Embed content in applications or websites
                                • 2. Share reports, dashboards, and apps
                                  • 3. Monitor usage and performance
                                    - Manage workspaces and assets
                                    • 1. Publish, update, and organize reports/datasets
                                      • 2. Manage data refresh and scheduled updates
                                        • 3. Create and configure workspaces
                                          Topic 3: Visualize and analyze data25-30%- Enhance reports with analytics
                                          • 1. Apply conditional formatting and custom visuals
                                            • 2. Use AI visuals, forecasts, and key influencers
                                              • 3. Create paginated reports
                                                - Perform data analysis
                                                • 1. Interpret results and identify trends
                                                  • 2. Create and manage bookmarks and tooltips
                                                    • 3. Implement custom visuals and R/Python scripts
                                                      - Create reports and dashboards
                                                      • 1. Design report layout, formatting, and interactivity
                                                        • 2. Choose appropriate visualizations
                                                          • 3. Apply filters, slicers, and drill-through
                                                            • 4. Create dashboards and pinned elements
                                                              Topic 4: Model the data25-30%- 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
                                                                      - Optimize model performance
                                                                      • 1. Reduce cardinality and data size
                                                                        • 2. Use aggregations and composite models
                                                                          • 3. Optimize relationships and calculations
                                                                            - Create model calculations
                                                                            • 1. Use CALCULATE and filter context
                                                                              • 2. Use DAX: calculated columns, calculated tables, measures
                                                                                • 3. Implement aggregation and time intelligence

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

                                                                                  Question #1
                                                                                  Power BI Desktop에서 보고서를 작성하고 있습니다. 모델에는 다음과 같은 테이블이 있습니다.

                                                                                  테이블들 사이에는 관계가 있습니다.
                                                                                  주문 금액, 주문 날짜, 전체 이름 순으로 표시되는 보고서를 Power BI 서비스에 게시할 계획입니다.
                                                                                  보고서 보기에는 보고서에 필요한 열만 표시되도록 해야 합니다. 또한, 게시되는 시맨틱 모델의 크기를 최소화해야 합니다.
                                                                                  Power BI Desktop에서 열을 어떻게 구성해야 합니까? 답변하려면 답변 영역에서 적절한 옵션을 선택하십시오.
                                                                                  참고: 정답 하나당 1점입니다.


                                                                                  Question #2
                                                                                  Power Query 편집기를 사용하여 Power BI Desktop으로 데이터를 가져옵니다.
                                                                                  전체 의미 모델은 250,000개의 행으로 구성됩니다. 모든 행은 다음 그림에 표시된 데이터 형식과 일치합니다.

                                                                                  테이블의 데이터 모델 크기를 최적화해야 합니다.
                                                                                  값 열과 날짜/시간 열에 어떤 데이터 형식을 사용해야 할까요? 정답을 선택하려면 답변란에서 적절한 옵션을 고르세요.
                                                                                  참고: 정답 하나당 1점입니다.


                                                                                  Question #3
                                                                                  참고: 이 문제는 동일한 시나리오를 제시하는 일련의 문제 중 하나입니다. 각 문제는 명시된 목표를 충족할 수 있는 고유한 답안을 포함하고 있습니다. 일부 문제 세트에는 정답이 두 개 이상 있을 수 있고, 다른 문제 세트에는 정답이 없을 수 있습니다.
                                                                                  이 섹션의 질문에 답변한 후에는 해당 섹션으로 돌아갈 수 없습니다. 따라서 해당 질문은 복습 화면에 표시되지 않습니다.
                                                                                  열이 포함된 데이터 소스가 있습니다. 열에는 대소문자를 구분하는 데이터가 포함되어 있습니다.
                                                                                  DirectQuery 모드에 Power BI 의미 모델이 있습니다.
                                                                                  모델에 연결한 결과, 정의되지 않은 값과 오류가 포함되어 있음을 발견했습니다.
                                                                                  문제를 해결해야 합니다.
                                                                                  해결 방법: 필요한 유형으로 값을 암묵적으로 변환합니다.
                                                                                  이것이 목표를 달성하는가?

                                                                                  A. 아니요
                                                                                  B. 네


                                                                                  Question #4
                                                                                  RPT1이라는 이름의 Power BI 보고서를 생성했는데, 이 보고서에는 매출 데이터가 포함되어 있습니다. 데이터는 1천만 행으로 구성되어 있으며, RPT1에는 15개의 시각화 요소가 있습니다.
                                                                                  사용자들은 RPT1이 로딩 속도가 느리다고 말합니다.
                                                                                  문제의 원인을 조사해야 합니다.
                                                                                  무엇을 사용해야 할까요?

                                                                                  A. 질의 진단
                                                                                  B. 파워 쿼리 편집기
                                                                                  C. 성능 분석기
                                                                                  D. DAX 쿼리 보기


                                                                                  Question #5
                                                                                  Microsoft Power BI를 사용하여 SalesDetail이라는 테이블의 데이터를 모델링하고 있습니다.
                                                                                  최종 사용자에게 SalesDetail 데이터에 대한 요약 통계 접근 권한을 제공해야 합니다. 사용자들은 데이터의 완전성 및 값 분포에 대한 통찰력을 필요로 합니다.
                                                                                  어떤 세 가지 행동을 순서대로 수행해야 할까요? 정답을 선택하려면, 행동 목록에서 적절한 행동을 골라 답란에 옮겨 올바른 순서대로 배열하세요.


                                                                                  Solutions:

                                                                                  Question #1
                                                                                  Correct Answer: Only visible for members
                                                                                  Question #2
                                                                                  Correct Answer: Only visible for members
                                                                                  Question #3
                                                                                  Correct Answer: A
                                                                                  Question #4
                                                                                  Correct Answer: C
                                                                                  Question #5
                                                                                  Correct Answer: Only visible for members

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