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所在平台: Udemy |
课程主页: https://www.udemy.com/course/dp-600-microsoft-fabric-analytics-engineer-associate-2024/
课程评论：没有评论
课程名称：DP-600 Microsoft Fabric Analytics Engineer Associate 2025 课程概述：本课程旨在帮助学生获得“Microsoft Certified: Fabric Analytics Engineer Associate”认证。课程通过实践测试评估您在Microsoft Azure上操作和维护分析解决方案的技能，内容涵盖DP-600考试的关键领域。主要测量技能包括：规划、实施及管理数据分析解决方案（10-15%）、准备和提供数据（40-45%）、实施和管理语义模型（20-25%）和探索与分析数据（20-25%）。 受众简介：作为此考试的候选人，您应具备使用Microsoft Fabric组件（如湖仓、数据仓库、笔记本、数据流、数据管道、语义模型和报告）设计、创建和部署企业级数据分析解决方案的专业知识。您的职责包括将数据转化为可重用的分析资产，实施分析最佳实践（如版本控制和部署），与解决方案架构师、数据工程师、数据科学家、AI工程师、数据库管理员和Power BI数据分析师等角色进行合作。您需要具备数据建模、数据转换、源控制、探索性分析等方面的经验，并掌握SQL、DAX和PySpark等语言。 实践测试的问题涵盖了以下关键领域：规划和管理数据分析环境；创建对象、复制/转换湖仓/数据仓库中的数据；优化管道、查询和Delta表的性能；设计、构建和优化语义模型；编写DAX计算和实施安全性；使用SQL查询数据并进行探索性分析。课程提供详细的解释和文档链接，将帮助您为DP-600考试及数据工程专家认证路径做好准备。祝您考试准备顺利！
Note: This course is designed for students who want to attain the "Microsoft Certified: Fabric Analytics Engineer Associate" certificationThis practice test will assess your skills in operationalizing and maintaining analytics solutions on Microsoft Azure, as measured by the DP-600 exam. The questions cover the key areas outlined by Microsoft:Skills measuredPlan, implement, and manage a solution for data analytics (10-15%)Prepare and serve data (40-45%)Implement and manage semantic models (20-25%)Explore and analyze data (20-25%)Audience Profile As a candidate for this exam, you should have expertise in designing, creating, and deploying enterprise-scale data analytics solutions using Microsoft Fabric components like lakehouses, data warehouses, notebooks, dataflows, data pipelines, semantic models, and reports.Your responsibilities include:Transforming data into reusable analytics assetsImplementing analytics best practices like version control and deploymentPartnering with roles like solution architects, data engineers, data scientists, AI engineers, DBAs, and Power BI data analystsYou need experience with data modeling, data transformation, source control, exploratory analytics, and languages like SQL, DAX, and PySpark.The practice questions cover key areas such as:Planning and managing data analytics environmentsCreating objects, copying/transforming data in lakehouses/warehousesOptimizing performance of pipelines, queries, and Delta tablesDesigning, building, and optimizing semantic modelsWriting DAX calculations and implementing securityQuerying data using SQL and performing exploratory analyticsWith thorough explanations and links to documentation, this course will prepare you for the DP-600 exam and the Data Engineer Expert certification path.All the best for your exam preparation!
