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

  • Exam Code: PL-300 Korean
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Korean Version)
  • Q & A: 472 Questions and Answers

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

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Microsoft PL-300 Korean Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft Power BI Data Analyst
Exam Number:PL-300
Real Exam Qty:40-60
Exam Duration:180 minutes
Exam Price:USD 165
Related Certifications:Microsoft Certified: Data Analyst Associate
Microsoft Certified: Power Platform Associate
Available Languages:Chinese (Traditional), Chinese (Simplified), Spanish, Russian, Italian, Portuguese (Brazil), Japanese, German, Arabic (Saudi Arabia), Indonesian, Korean, French, English
Certificate Validity Period:12 months
Passing Score:700 (out of 1000)
Exam Format:Performance-based, Case studies, Simulation, Drag and drop, Multiple choice (single/multiple response)
Recommended Training:Microsoft Learn - PL-300 Learning Path
Microsoft Official Course: PL-300T00
Exam Registration:Pearson VUE Registration
Microsoft Learn - Schedule Exam
Sample Questions:Free Download PL-300 Korean Exam PDF Torrent
Exam Way:Online proctored or onsite at Pearson VUE test centers
Pre Condition:No mandatory prerequisites; recommended experience: proficiency in Power Query, DAX, data profiling, and understanding of data security concepts
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/pl-300

Microsoft PL-300 Korean Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Manage and secure Power BI15-20%- 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
        - Manage workspaces and assets
        • 1. Manage data refresh and scheduled updates
          • 2. Publish, update, and organize reports/datasets
            • 3. Create and configure workspaces
              - Deploy and distribute content
              • 1. Share reports, dashboards, and apps
                • 2. Embed content in applications or websites
                  • 3. Monitor usage and performance
                    Topic 2: Model the data25-30%- 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. Create common date tables
                              • 3. Implement role-playing dimensions
                                • 4. Define tables, columns, and hierarchies
                                  - Create model calculations
                                  • 1. Implement aggregation and time intelligence
                                    • 2. Use CALCULATE and filter context
                                      • 3. Use DAX: calculated columns, calculated tables, measures
                                        Topic 3: Visualize and analyze data25-30%- Create reports and dashboards
                                        • 1. Design report layout, formatting, and interactivity
                                          • 2. Apply filters, slicers, and drill-through
                                            • 3. Create dashboards and pinned elements
                                              • 4. Choose appropriate visualizations
                                                - Perform data analysis
                                                • 1. Interpret results and identify trends
                                                  • 2. Create and manage bookmarks and tooltips
                                                    • 3. Implement custom visuals and R/Python scripts
                                                      - Enhance reports with analytics
                                                      • 1. Use AI visuals, forecasts, and key influencers
                                                        • 2. Create paginated reports
                                                          • 3. Apply conditional formatting and custom visuals
                                                            Topic 4: Prepare the data25-30%- Profile and clean data
                                                            • 1. Manage data types, columns, and rows
                                                              • 2. Evaluate data statistics and column properties
                                                                • 3. Transform data using Power Query Editor
                                                                  • 4. Resolve inconsistencies, null values, and errors
                                                                    - Load and configure data
                                                                    • 1. Configure data refresh settings
                                                                      • 2. Define table structures and properties
                                                                        • 3. Integrate data from multiple sources
                                                                          - Get or connect to data
                                                                          • 1. Create and modify parameters
                                                                            • 2. Identify and connect to data sources or shared semantic models
                                                                              • 3. Choose storage modes: Import, DirectQuery, DirectLake
                                                                                • 4. Configure data source settings, credentials, and privacy levels

                                                                                  Got Questions About the Microsoft Power BI Data Analyst (PL-300 Korean Version)? Start Here

                                                                                  Yes, the official recommendations are:

                                                                                  Courses are worth the time if you have it — and if you don't, they're not the only route. Busy candidates often go straight to the PL-300 Korean practice questions from TorrentVCE, which compress the exam's knowledge points into focused, time-saving practice.

                                                                                  Budget USD 165 for registration, and aim for 700 (out of 1000) to pass. Since the fee resets to full price on every retake, the cheapest strategy is preparation: work the 472 practice questions from TorrentVCE until the pass mark becomes your floor, not your ceiling.

                                                                                  The Microsoft Power BI Data Analyst (PL-300 Korean Version) leads to the Microsoft Certified: Power BI Data Analyst Associate certification at the Associate level. Employers notice it in interviews — it's shorthand for proven ability, and it often decides who reaches the final round. It also pairs with related credentials like Microsoft Certified: Data Analyst Associate, Microsoft Certified: Power Platform Associate if you plan to keep climbing.

                                                                                  There is. The free PDF demo shows exactly what you're buying — real questions, real answer quality. After purchase, 365 days of free updates keep the material current, and renewing an expired update period costs 50% of the price through your member zone.

                                                                                  The Microsoft Power BI Data Analyst (PL-300 Korean Version) blueprint spans 4 domains, including Visualize and analyze data (25-30%), Model the data (25-30%), Prepare the data (25-30%). Those percentages are the vendor telling you where the points are — spend your limited study hours accordingly. The complete outline above breaks down every subtopic.

                                                                                  Use the vendor's official registration channels listed here:

                                                                                  Also worth noting when you book: the PL-300 Korean exam is delivered Online proctored or onsite at Pearson VUE test centers, so factor that into your choice of test date and location.

                                                                                  No mandatory prerequisites; recommended experience: proficiency in Power Query, DAX, data profiling, and understanding of data security concepts Because eligibility rules change over time, treat the vendor as the final authority — check the official PL-300 Korean requirements before paying any fees.

                                                                                  The exam packs 40-60 questions into 180 minutes. Busy professionals, take note: the time pressure is real but trainable. Set a pace target per question, practice skipping without guilt, and run timed mock exams in the TorrentVCE engine until finishing on time becomes a habit rather than a hope.

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

                                                                                  Question #1

                                                                                  매출 테이블에는 오늘 날짜까지 지난 5년간의 일별 매출 기록이 포함되어 있습니다.
                                                                                  2022년 3월을 선택했을 때 2021년 3월의 총 매출액을 반환하는 측정값을 만들 계획입니다.
                                                                                  어떤 DAX 표현식을 사용해야 할까요?

                                                                                  • A. CALCULATE(SUM(Sales[Sales]), SAMEPERIODLASTYEAR(DimDate[Date] ))
                                                                                  • B. TOTALYTD(SUM(Sales[Sales]), DimDate[Date] )
                                                                                  • C. CALCULATE(SUM(Sales[Sales]), PREVIOUSYEAR(DimDate[Date] ))
                                                                                  • D. SUM(Sales[Sales])
                                                                                  Reveal Solution  Discussion  0

                                                                                  Correct Answer: A  🗳️

                                                                                  Explanation: Only visible for TorrentVCE members. You can sign-up / login (it's free).

                                                                                  Question #2

                                                                                  다음 그림과 같이 Power BI 데이터 모델이 있습니다.

                                                                                  Reveal Solution  Discussion  0

                                                                                  Correct Answer:


                                                                                  Explanation:
                                                                                  The retained answer-area mapping contains the correct selections. Begin with the scenario statement that you have the power bi data model shown in the following exhibit. The opposite cardinality or unnecessary bidirectional filtering can duplicate results, block propagation, or create ambiguity rather than solve the stated model path. The relationship must carry filters from the descriptive table to the transaction table through matching keys. Bidirectional filtering is reserved for a demonstrated need because it can introduce multiple active paths. In Microsoft ' s current exam outline, the corresponding objective is " Define a relationship ' s cardinality and cross-filter direction " . It also preserves predictable filter context and aggregation behavior when the result is used by several visuals or report pages.
                                                                                  Microsoft Learn reference: https://learn.microsoft.com/en-us/power-bi/transform-model/desktop- relationships-understand | PL-300 objective: " Define a relationship ' s cardinality and cross-filter direction "
                                                                                  | Study guide: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/pl-300

                                                                                  Question #3

                                                                                  Power BI 모델에 다음과 같은 테이블이 있습니다.
                                                                                  제품 (제품 ID, 제품 이름)
                                                                                  매출 정보 (주문 ID, 주문 날짜, 제품 ID, 판매 담당자 ID, 매출 금액)
                                                                                  영업사원 (영업사원 ID, 영업사원 이름, 주소)
                                                                                  다음과 같은 측정값을 생성할 계획입니다.
                                                                                  Measure1 = DISTINCTCOUNT(Sales[ProductID])
                                                                                  다음과 같은 관계를 생성해야 합니다.
                                                                                  제품 판매
                                                                                  판매원에게 판매
                                                                                  이 솔루션은 Measure1을 사용하여 각 영업 사원이 판매한 제품 수를 표시할 수 있도록 해야 합니다.
                                                                                  관계를 어떻게 구성해야 할까요? 답변하려면 답변 영역에서 적절한 옵션을 선택하세요.
                                                                                  참고: 정답 하나당 1점입니다.

                                                                                  Reveal Solution  Discussion  0

                                                                                  Correct Answer:


                                                                                  Explanation:

                                                                                  The technical decision turns on how to create the following relationships: Sales to Product Sales to Salesperson The solution must ensure that you can use Measure1 to display the count of products sold. The selections in the retained answer exhibit are the verified configuration. The relationship must carry filters from the descriptive table to the transaction table through matching keys. Bidirectional filtering is reserved for a demonstrated need because it can introduce multiple active paths. The opposite cardinality or unnecessary bidirectional filtering can duplicate results, block propagation, or create ambiguity rather than solve the stated model path. The current PL-300 study guide places this under the objective " Define a relationship ' s cardinality and cross-filter direction " .
                                                                                  Microsoft Learn reference: https://learn.microsoft.com/en-us/power-bi/transform-model/desktop- relationships-understand | PL-300 objective: " Define a relationship ' s cardinality and cross-filter direction "
                                                                                  | Study guide: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/pl-300

                                                                                  Question #4

                                                                                  Power Query 편집기를 사용하여 고객 피드백 데이터를 미리 볼 수 있습니다.
                                                                                  고객 피드백을 기반으로 향상된 데이터 열을 추가하려면 AI Insights를 사용해야 합니다. 솔루션은 다음 사항을 식별해야 합니다.
                                                                                  고객들이 가장 자주 피드백을 제공하는 내용은 무엇인가요?
                                                                                  고객들이 귀사 제품을 좋아하는지 여부
                                                                                  피드백의 언어
                                                                                  각 출력에 어떤 AI Insights 서비스를 사용해야 할까요? 정답을 확인하려면 적절한 서비스를 해당 출력으로 드래그하세요. 각 서비스는 한 번, 여러 번 또는 전혀 사용하지 않을 수 있습니다. 콘텐츠를 보려면 창 사이의 분할 막대를 드래그하거나 스크롤해야 할 수도 있습니다.
                                                                                  참고: 정답 하나당 1점입니다.

                                                                                  Reveal Solution  Discussion  0

                                                                                  Correct Answer:


                                                                                  Explanation:

                                                                                  The retained answer-area mapping contains the correct selections. The scenario is asking for a way to apply AI Insights services that extract recurring topics, sentiment, and language from customer feedback. A visual, measure, or model relationship cannot repair the incoming tabular shape; those features operate after the query result has already been loaded. This is a shaping operation in Power Query. Performing it in the applied steps produces correctly typed, named, and structured columns before loading, which keeps report and model logic focused on analysis. In Microsoft ' s current exam outline, the corresponding objective is " Create and transform columns " . This keeps the query output reproducible at refresh and leaves the semantic model with the grain and schema required by the report.
                                                                                  Microsoft Learn reference: https://learn.microsoft.com/en-us/power-query/best-practices | PL-300 objective: " Create and transform columns " | Study guide: https://learn.microsoft.com/en-us/credentials/certifications
                                                                                  /resources/study-guides/pl-300

                                                                                  Question #5

                                                                                  Power BI 시맨틱 모델에 Opportunity라는 테이블이 있습니다.
                                                                                  기회 테이블에는 자격이라는 이름의 열이 있습니다.
                                                                                  자격 요건 열에는 0에서 V 사이의 값이 포함됩니다.
                                                                                  기회를 낮음, 중간, 높음의 척도로 평가하는 새로운 측정 기준을 만들어야 합니다.
                                                                                  DAX 수식을 어떻게 완성해야 합니까? 답하려면 답변 영역에서 적절한 옵션을 선택하십시오.
                                                                                  참고: 정답 하나당 1점입니다.

                                                                                  Reveal Solution  Discussion  0

                                                                                  Correct Answer:


                                                                                  Explanation:

                                                                                  What determines the answer is the need to build a new measure to score the opportunities on a scale of low, medium, and high. The verified expression produces the requested scalar result under report filtering. It uses model relationships and DAX context semantics instead of shifting a dynamic calculation into a static source or calculated column. Use the selections preserved in the answer exhibit as the supported configuration. An alternative that changes the source or creates a stored column either ignores filter context or increases model size without meeting a dynamic measure requirement. Microsoft lists this skill in the current PL-300 outline as " Create single aggregation measures " .
                                                                                  Microsoft Learn reference: https://learn.microsoft.com/en-us/dax/ | PL-300 objective: " Create single aggregation measures " | Study guide: https://learn.microsoft.com/en-us/credentials/certifications/resources
                                                                                  /study-guides/pl-300

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