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所在平台: Udemy |
课程主页: https://www.udemy.com/course/azure-dp-900-certification-prep/
课程评论：没有评论
课程名称：DP-900 Azure数据基础认证准备一天四套 概述：欢迎参加DP-900课程，这是针对微型软Azure数据基础认证的最佳质量练习测试，旨在帮助您在不额外投入精力的情况下准备DP-900考试。本课程适合对云计算感兴趣并希望了解Azure如何处理数据存储、处理和分析的个人；同时，数据分析师、数据库管理员和数据工程师等各种与数据相关工作的专业人士，或希望转入数据相关角色的非技术背景专业人士，都可以从中受益。练习测试能够评估您备考的准备情况，通过模拟考试，您可以衡量当前知识水平，并找到需要进一步学习的领域。练习测试能够强调您的优势和弱点，通过回顾错误回答的问题，您可以集中精力改善特定主题的学习。参与练习测试可以提供真实的考试体验，使您对DP-900考试中可能遇到的问题类型、措辞和难度等级更加熟悉。成功完成练习测试可以提升您的信心和动力，随着分数和对材料理解的提高，您会感到更有准备参加实际考试。练习测试还帮助您提升时间管理技巧，通过模拟DP-900考试的时间限制，从而提高考试当天的效率。高分通过练习测试则能确认您对Azure数据基础的理解，并验证您的准备工作，是您朝着DP-900认证进步的具体现实衡量。 技能测评： - 描述核心数据概念（25-30%） - 确定Azure关系数据的考虑因素（20-25%） - 描述使用Azure处理非关系数据的考虑因素（15-20%） - 描述Azure上的分析工作负载（25-30%） 功能模块： - 核心数据概念（25-30%）：数据表示方式、结构化和非结构化数据的特性，数据存储选项及数据工作负载的职责等。 - Azure关系数据（20-25%）：关系概念、规范化及常用SQL语句，Azure SQL产品家族等。 - Azure非关系数据（15-20%）：Azure存储能力，Azure Blob存储、Azure Cosmos DB的功能与用例等。 - Azure分析工作负载（25-30%）：大规模分析的常见元素，数据可视化在Microsoft Power BI中的应用等。 通过本课程的学习，您将能够掌握Azure数据基础的核心内容，为DP-900认证考试做好充分的准备。
Welcome to the best quality DP-900: Microsoft Azure Data Fundamentals Certification practice tests to help you prepare for your DP-900 exam without any extra effort. Individuals curious about cloud computing and eager to understand how Azure handles data storage, processing, and analytics or those working with data in various capacities, such as data analysts, database administrators, and data engineers, who want to understand Azure data solutions or Professionals from non-technical backgrounds or other IT domains looking to transition into data-centric roles, where knowledge of Azure data fundamentals is valuable. Practice tests help assess your readiness for the actual DP-900 exam. By simulating this test exam , you can gauge your current level of knowledge and identify areas that require further study. Practice tests highlight areas of strength and weakness. By reviewing the questions you answered incorrectly, you can focus your study efforts on specific topics that need improvement. Engaging with practice tests provides a realistic exam experience, allowing you to become comfortable with the types of questions, wording, and difficulty level you'll encounter on the DP-900 exam.Successfully completing practice tests can boost your confidence and motivation. As you see improvement in your scores and understanding of the material, you'll feel more prepared to tackle the actual exam.Practice tests help you refine your time management skills by simulating the time constraints of the DP-900 exam. Learning to pace yourself during practice can enhance your efficiency on exam day.Achieving high scores on practice tests confirms your understanding of Azure data fundamentals and validates your preparation efforts. It's a tangible measure of your progress towards DP-900 certification.Skills measured· Describe core data concepts (25-30%)· Identify considerations for relational data on Azure (20-25%)· Describe considerations for working with non-relational data on Azure (15-20%)· Describe an analytics workload on Azure (25-30%)Functional groupsDescribe core data concepts (25-30%)Describe ways to represent data· Describe features of structured data· Describe features of semi-structured· Describe features of unstructured dataIdentify options for data storage· Describe common formats for data files· Describe types of databasesDescribe common data workloads· Describe features of transactional workloads· Describe features of analytical workloadsIdentify roles and responsibilities for data workloads· Describe responsibilities for database administrators· Describe responsibilities for data engineers· Describe responsibilities for data analystsIdentify considerations for relational data on Azure (20-25%)Describe relational concepts· Identify features of relational data· Describe normalization and why it is used· Identify common structured query language (SQL) statements· Identify common database objectsDescribe relational Azure data services· Describe the Azure SQL family of products including Azure SQL Database, Azure SQL· Managed Instance, and SQL Server on Azure Virtual Machines· Identify Azure database services for open-source database systemsDescribe considerations for working with non-relational data on Azure (15-20%)Describe capabilities of Azure storage· Describe Azure Blob storage· Describe Azure File storage· Describe Azure Table storageDescribe capabilities and features of Azure Cosmos DB· Identify use cases for Azure Cosmos DB· Describe Azure Cosmos DB APIsDescribe an analytics workload on Azure (25-30%)Describe common elements of large-scale analytics· Describe considerations for data ingestion and processing· Describe options for analytical data stores· Describe Azure services for data warehousing, including Azure Synapse Analytics, Azure Databricks, Azure HDInsight, and Azure Data FactoryDescribe consideration for real-time data analytics· Describe the difference between batch and streaming data· Describe technologies for real-time analytics including Azure Stream Analytics, Azure Synapse Data Explorer, and Spark structured streamingDescribe data visualization in Microsoft Power BI· Identify capabilities of Power BI· Describe features of data models in Power BI· Identify appropriate visualizations for data
