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PL-300日本語 Online Test Engine

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PL-300日本語 PDF Practice Q&A's

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  • Total Questions: 472
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Many candidates ask us how to tell good materials from shoddy ones, and our answer is always the same: look before you pay. The free demo of the PL-300日本語 exam product at ITCertMagic shows real sample questions with expert-verified answers, so the quality of the Microsoft Power BI Data Analyst (PL-300日本語版) materials is something you verify, not something you are told.

Microsoft PL-300日本語 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft Power BI Data Analyst
Exam Number:PL-300
Passing Score:700 (out of 1000)
Exam Format:Simulation, Multiple choice (single/multiple response), Performance-based, Drag and drop, Case studies
Available Languages:Chinese (Traditional), Spanish, German, English, French, Portuguese (Brazil), Chinese (Simplified), Italian, Arabic (Saudi Arabia), Indonesian, Korean, Russian, Japanese
Exam Duration:180 minutes
Related Certifications:Microsoft Certified: Data Analyst Associate
Microsoft Certified: Power Platform Associate
Exam Price:USD 165
Certificate Validity Period:12 months
Real Exam Qty:40-60
Recommended Training:Microsoft Official Course: PL-300T00
Microsoft Learn - PL-300 Learning Path
Exam Registration:Pearson VUE Registration
Microsoft Learn - Schedule Exam
Sample Questions: DOWNLOAD DEMO
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日本語 Exam Syllabus Topics:

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

                                                                                  Answering Your Questions About the Microsoft Power BI Data Analyst (PL-300日本語版) Exam

                                                                                  Check three things. First, authorship: the Microsoft Power BI Data Analyst (PL-300日本語版) questions at ITCertMagic are developed by experts with long experience in this field, and every answer is verified before publication. Second, update discipline: the bank is revised at high frequency, because exam content never stands still. Third, transparency: a free demo lets you inspect real sample questions and the practice interface before paying. Materials that cannot survive those three checks are not worth your money — ours are built to pass them.

                                                                                  The passing score for the PL-300日本語 exam is 700 (out of 1000), and the registration fee is USD 165. With the fee paid per attempt, thorough preparation is the economical route — consistent timed practice until your scores stay above the passing mark.

                                                                                  The PL-300日本語 exam is the official examination for the Microsoft Power BI Data Analyst (PL-300日本語版) certification from Microsoft. It measures whether you can apply the published exam objectives to realistic working scenarios, and in a job market where enterprises keep raising requirements, the resulting credential is a clear, verifiable advantage — for job seekers and for employees aiming at the next step alike.

                                                                                  According to the official outline, the PL-300日本語 exam is structured around weighted domains such as:

                                                                                  • Visualize and analyze data (25-30%)
                                                                                  • Manage and secure Power BI (15-20%)
                                                                                  • Prepare the data (25-30%)

                                                                                  Because the exam evolves, the Microsoft Power BI Data Analyst (PL-300日本語版) practice materials at ITCertMagic are updated frequently — and the latest version is emailed to you automatically whenever a revision is released during your update period.

                                                                                  Official registration for the PL-300日本語 exam is available through:

                                                                                  Choose a date that leaves room for a full round of timed practice beforehand — the deadline itself is a powerful study tool.

                                                                                  The PL-300日本語 exam presents 40-60 questions within 180 minutes minutes. Rehearsing complete sets under the same time cap trains both accuracy and pacing, and it is the fastest way to find out which domains still need work.

                                                                                  Yes — user experience begins before checkout here. Download the free demo of the PL-300日本語 exam product to browse real sample content, see how the expert-verified answers are presented, and get a feel for the practice interface. After that preview, the decision is fully yours: if the materials fit, the full package is a one-minute checkout away; if not, the demo cost you nothing. Every demo at ITCertMagic is free of charge.

                                                                                  Microsoft lists these training resources for candidates:

                                                                                  Official training builds the knowledge; frequent practice with an up-to-date question bank builds the exam-day readiness. The two reinforce each other well.

                                                                                  No mandatory prerequisites; recommended experience: proficiency in Power Query, DAX, data profiling, and understanding of data security concepts

                                                                                  Microsoft Power BI Data Analyst (PL-300日本語版) Sample Questions:

                                                                                  注:この問題は、同じシナリオを提示する一連の問題の一部です。便宜上、シナリオは各問題で繰り返されます。各問題では目標と選択肢が異なりますが、シナリオの文章はシリーズ全体で全く同じです。
                                                                                  繰り返しシナリオの開始
                                                                                  Microsoft SQL Server データベースがあり、データベース図の図に示されているテーブルが含まれています。(図をクリックしてください。)

                                                                                  Power BI モデル図(図をクリックしてください)に示されているような Power BI モデルを開発する予定です。

                                                                                  Power BIを使用して、2013年から2015年までのデータをインポートする予定です。
                                                                                  製品サブカテゴリ[Subcategory]にはNULL値が含まれています。
                                                                                  繰り返しのシナリオ終了。
                                                                                  Power BIモデルを実装します。
                                                                                  Power BI の目的のモデルに合うように、製品カテゴリテーブルのクエリを編集する必要があります。
                                                                                  高度なクエリをどのように完了すればよいですか?回答するには、適切な値を正しいターゲットにドラッグしてください。
                                                                                  各値は、1回だけ使用することも、複数回使用することも、全く使用しないこともできます。
                                                                                  コンテンツを表示するには、ペイン間の分割バーをドラッグするか、スクロールする必要がある場合があります。
                                                                                  注:正解ごとに1ポイントが加算されます。

                                                                                  Reveal Solution  Discussion  0

                                                                                  Correct Answer:


                                                                                  Explanation:

                                                                                  The completed mapping shown in the answer area is correct. The scenario is asking for a way to edit the Product Category table query to match the desired Power BI model. The M transformation belongs in the query pipeline, where source values can be cleaned, split, filled, renamed, or typed consistently. A report visual or DAX measure would operate too late in the process. This directly matches the current study-guide objective " Resolve inconsistencies, unexpected or null values, and data quality issues " . A visual, measure, or model relationship cannot repair the incoming tabular shape; those features operate after the query result has already been loaded.
                                                                                  Microsoft Learn reference: https://learn.microsoft.com/en-us/power-query/best-practices | PL-300 objective: " Resolve inconsistencies, unexpected or null values, and data quality issues " | Study guide: https://learn.
                                                                                  microsoft.com/en-us/credentials/certifications/resources/study-guides/pl-300

                                                                                  Power BI Desktop でセマンティック モデルを作成する必要があります。ソリューションは以下の要件を満たす必要があります。
                                                                                  モデルには、注文ごとに1行を持つ「Orders」という名前のテーブルが含まれている必要があります。各行には、注文ごとの合計金額が含まれます。
                                                                                  注文は、選択された顧客IDの値に基づいてフィルタリングする必要があります。
                                                                                  ユーザーはリストから顧客IDの値を選択する必要があります。
                                                                                  顧客リストはODataソースから取得する必要があります。
                                                                                  Power Query エディターで作成すべきオブジェクトはどれですか?正解はそれぞれ、解決策の一部を示しています。
                                                                                  注:正解ごとに1ポイントが加算されます。

                                                                                  • A. 顧客リストを含む単一の列を持つ注文クエリ
                                                                                  • B. 顧客IDのパラメータで、手動で入力された値を使用して候補値を設定します。
                                                                                  • C. 顧客IDでフィルタリングされた顧客クエリ
                                                                                  • D. クエリを使用して推奨値を設定するCustomerIDのパラメータ
                                                                                  • E. CustomerIDでフィルタリングされた注文クエリ
                                                                                  • F. 顧客IDのリストを含む単一の列を持つ顧客クエリ
                                                                                  Reveal Solution  Discussion  0

                                                                                  Correct Answer: D,E,F  🗳️

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

                                                                                  データモデルを作成する前に、データの懸念事項に対処する必要があります。Power Queryエディターでは、どのような操作を行うべきでしょうか?

                                                                                  • A. sales_amount 列を変換して、負の値を 0 に置き換えます。
                                                                                  • B. 列プロファイルを選択し、次に sales_amount 列を選択します。
                                                                                  • C. sales_amount列を選択し、数値フィルターを適用します。
                                                                                  • D. 列分布を選択します。
                                                                                  Reveal Solution  Discussion  0

                                                                                  Correct Answer: B  🗳️

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

                                                                                  Microsoft Power BI Desktop を使用して Power Query エディターでデータをプロファイリングしています。テーブルデータは次の図のように表示されます。

                                                                                  図に示された情報に基づいて、各記述を完成させる選択肢をドロップダウンメニューを使用して選択してください。
                                                                                  注:正解ごとに1ポイントが加算されます。

                                                                                  Reveal Solution  Discussion  0

                                                                                  Correct Answer:


                                                                                  Explanation:

                                                                                  The retained answer-area mapping contains the correct selections. Begin with the scenario statement that you are using microsoft power bi desktop to profile data in power query editor. table data is displayed as shown in the following exhibit. use the drop-down menus to select. A visual, measure, or model relationship cannot repair the incoming tabular shape; those features operate after the query result has already been loaded. Power Query should resolve this requirement before the data enters the semantic model. The chosen transformation preserves the required rows and grain while converting the source layout into an analysis-ready table. In Microsoft ' s current exam outline, the corresponding objective is " Evaluate data, including data statistics and column properties " .
                                                                                  Microsoft Learn reference: https://learn.microsoft.com/en-us/power-query/best-practices | PL-300 objective: " Evaluate data, including data statistics and column properties " | Study guide: https://learn.microsoft.com/en- us/credentials/certifications/resources/study-guides/pl-300

                                                                                  あなたは、erp1という名前のAzure SQLデータベースのデータを使用するPower BIレポートを作成しています。
                                                                                  以下のテーブルをインポートします。

                                                                                  以下の分析を実施する必要があります。
                                                                                  ; 一定期間にわたって販売された注文には、注文総額の指標が含まれます。
                                                                                  販売された製品の属性による注文
                                                                                  レポート内のビジュアルを操作する際の更新時間を最小限に抑えるソリューションが必要です。まず最初に何をすべきでしょうか?

                                                                                  • A. DAX関数を使用して、注文テーブルに製品カテゴリのリストを追加する計算列を作成します。
                                                                                  • B. Power Query から、注文明細クエリと製品クエリをマージします。
                                                                                  • C. Power Query から、Orders クエリと Order Line Hems クエリをマージします。
                                                                                  • D. DAX関数を使用して、製品ごとの注文数を計算します。
                                                                                  Reveal Solution  Discussion  0

                                                                                  Correct Answer: C  🗳️

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

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