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所在平台: Udemy |
课程主页: https://www.udemy.com/course/practice-set-fabric-analytics-engineer-dp-600-exam/
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课程名称：实践集：Fabric 分析工程师 (DP-600) 考试 课程概述：欢迎参加实践集：Fabric 分析工程师 (DP-600)！作为一名 Fabric 分析工程师助理，您需要具备设计、创建和部署企业级数据分析解决方案的专业知识。本课程专为帮助您准备微软 DP-600 - Fabric 分析工程师认证考试而设计。通过本课程，您将掌握以下核心 Fabric 组件，以应对实际挑战：Lakehouse、数据仓库、Notebook、数据流、数据管道、语义模型和报告。在成为 Fabric 分析工程师的过程中，您将与多位专业人士密切合作，包括解决方案架构师、数据工程师、数据科学家、人工智能工程师、数据库管理员和 Power BI 数据分析师。 除了掌握 Fabric 平台外，您还将深入了解以下关键领域：数据建模、数据转换技术、基于 Git 的源控制和探索性分析，以及 SQL、DAX 和 PySpark 等主要编程语言。通过实践练习和课程提供的全面见解，准备迎接 DP-600 认证考试，提升您的技能。让我们共同踏上这段学习旅程吧！ 测量技能： - 规划、实施和管理数据分析解决方案 - 准备和提供数据 - 实施和管理语义模型 - 探索和分析数据 适合对象：数据分析师、数据工程师、数据科学家。
Welcome to the Practice Set: Fabric Analytics Engineer (DP-600)! As a Fabric analytics engineer associate, you should have subject matter expertise in designing, creating, and deploying enterprise-scale data analytics solutions. These practice sets are specially designed to give you feel of Microsoft's DP-600 - Fabric Analytics Engineer certification exam.As a candidate preparing for this certification, you'll be equipped to tackle real-world challenges by mastering the following Fabric components:LakehouseData warehouseNotebookDataflowData pipelineSemantic modelReportIn your journey to becoming a Fabric Analytics Engineer, you'll collaborate closely with various professionals, including:Solution ArchitectData EngineerData ScientistAI EngineerDatabase AdministratorPower BI Data AnalystBeyond mastering the Fabric platform, this course will also immerse you in crucial areas such as:Data modelingData transformation techniquesGit-based source controlExploratory analyticsKey programming languages like SQL, DAX, and PySparkPrepare yourself to excel in the EXAM DP-600 certification by honing your skills through practical exercises and comprehensive insights provided in this course. Let's embark on this learning journey together!Skills measuredPlan, implement, and manage a solution for data analyticsPrepare and serve dataImplement and manage semantic modelsExplore and analyze dataWho this course is for:Data AnalystData EngineerData Scientist
