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所在平台: Udemy |
课程主页: https://www.udemy.com/course/ms_dp_900/
课程评论：没有评论
课程名称：Microsoft Azure 数据 (DP-900) 考试问题（2025年5月） 课程概述： 本课程旨在帮助学员掌握与Microsoft Azure相关的数据核心概念和考量，内容覆盖了多个重要领域。课程主要分为以下几个模块： 1. **核心数据概念（25-30%）** - 描述数据的表达方式 - 理解结构化数据、半结构化数据和非结构化数据的特点 - 识别数据存储选项和常见数据文件格式 - 了解数据库类型及相关的工作负载特征，包括事务性和分析性工作负载 - 确定为不同数据工作负载的相关角色和责任，如数据库管理员、数据工程师和数据分析师 2. **Azure中的关系型数据考量（20-25%）** - 理解关系型数据的概念和特征 - 学习归一化的原理及其应用 - 熟悉常用SQL语句和数据库对象 - 了解Azure中关系型数据服务，包括Azure SQL产品系列及其功能 3. **Azure中的非关系型数据考量（15-20%）** - 描述Azure存储的能力，包括Blob存储、文件存储和表存储 - 理解Azure Cosmos DB的用例及其API 4. **Azure中的分析工作负载（25-30%）** - 描述大规模分析的常见元素和数据摄取及处理的考虑事项 - 探索分析数据存储的选项及与微软云服务相关的内容，包括Azure Databricks和Microsoft Fabric - 区分批量和流数据，了解实时分析的服务 - 使用Microsoft Power BI进行数据可视化，包括数据模型的特性和适当的可视化选项 通过这个课程，学员将能够全面了解Azure数据平台的关键组成部分，为DP-900考试做好充分准备。
Skills at a glanceDescribe 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%)Describe core data concepts (25-30%)Describe ways to represent dataDescribe features of structured dataDescribe features of semi-structuredDescribe features of unstructured dataIdentify options for data storageDescribe common formats for data filesDescribe types of databasesDescribe common data workloadsDescribe features of transactional workloadsDescribe features of analytical workloadsIdentify roles and responsibilities for data workloadsDescribe responsibilities for database administratorsDescribe responsibilities for data engineersDescribe responsibilities for data analystsIdentify considerations for relational data on Azure (20-25%)Describe relational conceptsIdentify features of relational dataDescribe normalization and why it is usedIdentify common structured query language (SQL) statementsIdentify common database objectsDescribe relational Azure data servicesDescribe the Azure SQL family of products including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual MachinesIdentify Azure database services for open-source database systemsDescribe considerations for working with non-relational data on Azure (15-20%)Describe capabilities of Azure storageDescribe Azure Blob storageDescribe Azure File storageDescribe Azure Table storageDescribe capabilities and features of Azure Cosmos DBIdentify use cases for Azure Cosmos DBDescribe Azure Cosmos DB APIsDescribe an analytics workload (25-30%)Describe common elements of large-scale analyticsDescribe considerations for data ingestion and processingDescribe options for analytical data storesDescribe Microsoft cloud services for large-scale analytics, including Azure Databricks and Microsoft FabricDescribe consideration for real-time data analyticsDescribe the difference between batch and streaming dataIdentify Microsoft cloud services for real-time analyticsDescribe data visualization in Microsoft Power BIIdentify capabilities of Power BIDescribe features of data models in Power BIIdentify appropriate visualizations for data
