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所在平台: Udemy |
课程主页: https://www.udemy.com/course/pl-300-microsoft-power-bi-data-analyst-practice-exam-w/
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课程名称：PL-300 Microsoft Power BI 数据分析师实践考试：2025 课程概述：本课程提供的练习题非常适合打算参加 PL-300 考试的考生，帮助考生了解 Microsoft Power BI 数据分析师（PL-300）真实考试的题型。该考试的详细信息如下：考试名称：Microsoft Certified - Power BI Data Analyst Associate，考试代码：PL-300，考试费用：165 美元，题目数量：最多 40-60 道题目，题型包括单选题和多选题、拖放题及基于表现的题目，考试时长：180 分钟。该考试提供英语、德语和日语版本，及及格分数为 700 / 1000 分。 考试内容包括以下几个方面： 1. 数据准备（25-30%）： - 从数据源获取数据及连接设置 - 数据清洗与评估数据质量 - 转换和加载数据 - 设计星型架构及创建合适的关系 2. 数据建模（25-30%）： - 设计和实现数据模型，配置表和列属性 - 实施行级安全角色及 DAX 计算 - 优化模型性能 3. 数据可视化与分析（25-30%）： - 创建和格式化报告 - 应用自定义视觉和主题 - 使用 Power BI 的分析特性识别模式与趋势 4. 部署与维护资产（15-20%）： - 创建和管理工作区及资产 - 配置工作区应用及数据警报 - 为数据集提供访问权限 该考试的候选人通过利用可用数据和专业领域知识，提供可操作的见解。他们通过易于理解的数据可视化，创造有意义的商业价值，并使他人能够进行自助分析，部署和配置解决方案以供使用。Power BI 数据分析师与企业利益相关者紧密合作，识别业务需求，并与企业数据分析师及数据工程师协作，获取和转换数据，创建数据模型，进行数据可视化，最后利用 Power BI 共享资产。
These practice questions are ideal if you intend to take the PL-300 Exam and want to see what kinds of questions will be on the Microsoft Power BI Data Analyst (PL-300) - Real Exam.Microsoft Power BI Data Analyst (PL-300) Certification Practice Exam details:Exam Name: Microsoft Certified - Power BI Data Analyst AssociateExam Code: PL-300Exam Fee $165 (USD)Number of Questions: Maximum of 40-60 questions,Type of Questions: Multiple Choice Questions (single and multiple response), drag and drops and performance-based,Length of Test: 180 Minutes. The exam is available in English, German, and Japanese languages.Passing Score 700 / 1000Languages: English at launch.Schedule Exam: Pearson VUEMicrosoft Power BI Data Analyst (PL-300) Certification Exams skill questions:#) Prepare the data (25-30%)Get data from data sourcesIdentify and connect to a data sourceChange data source settings, including credentials, privacy levels, and data source locationsSelect a shared dataset, or create a local datasetChoose between DirectQuery, Import, and Dual modeChange the value in a parameterClean the dataEvaluate data, including data statistics and column propertiesResolve inconsistencies, unexpected or null values, and data quality issuesResolve data import errorsTransform and load the dataSelect appropriate column data typesCreate and transform columnsTransform a queryDesign a star schema that contains facts and dimensionsIdentify when to use reference or duplicate queries and the resulting impactMerge and append queriesIdentify and create appropriate keys for relationshipsConfigure data loading for queries#) Model the data (25-30%)Design and implement a data modelConfigure table and column propertiesImplement role-playing dimensionsDefine a relationship's cardinality and cross-filter directionCreate a common date tableImplement row-level security rolesCreate model calculations by using DAXCreate single aggregation measuresUse CALCULATE to manipulate filtersImplement time intelligence measuresIdentify implicit measures and replace with explicit measuresUse basic statistical functionsCreate semi-additive measuresCreate a measure by using quick measuresCreate calculated tablesOptimize model performanceImprove performance by identifying and removing unnecessary rows and columnsIdentify poorly performing measures, relationships, and visuals by using Performance AnalyzerImprove performance by choosing optimal data typesImprove performance by summarizing data#) Visualize and analyze the data (25-30%)Create reportsIdentify and implement appropriate visualizationsFormat and configure visualizationsUse a custom visualApply and customize a themeConfigure conditional formattingApply slicing and filteringConfigure the report pageUse the Analyze in Excel featureChoose when to use a paginated reportEnhance reports for usability and storytellingConfigure bookmarksCreate custom tool-tipsEdit and configure interactions between visualsConfigure navigation for a reportApply sortingConfigure sync slicersGroup and layer visuals by using the Selection paneDrill down into data using interactive visualsConfigure export of report content, and perform an exportDesign reports for mobile devicesIncorporate the Q & A feature in a reportIdentify patterns and trendsUse the Analyze feature in Power BIUse grouping, binning, and clusteringUse AI visualsUse reference lines, error bars, and forecastingDetect outliers and anomaliesCreate and share scorecards and metrics#) Deploy and maintain assets (15-20%)Create and manage work-spaces and assetsCreate and configure a workspaceAssign workspace rolesConfigure and update a workspace appPublish, import, or update assets in a workspaceCreate dashboardsChoose a distribution methodApply sensitivity labels to workspace contentConfigure subscriptions and data alertsPromote or certify Power BI contentManage global options for filesManage datasetsIdentify when a gateway is requiredConfigure a dataset scheduled refreshConfigure row-level security group membershipProvide access to datasetsCandidates for this exam deliver actionable insights by working with available data and applying domain expertise. They provide meaningful business value through easy-to-comprehend data visualizations, enable others to perform self-service analytics, and deploy and configure solutions for consumption.The Power BI data analyst works closely with business stakeholders to identify business requirements. They collaborate with enterprise data analysts and data engineers to identify and acquire data. They also transform the data, create data models, visualize data, and share assets by using Power BI.
