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所在平台: Udemy |
课程主页: https://www.udemy.com/course/master-the-dp-700-exam-microsoft-fabric-data-engineer-pract/
课程评论：没有评论
课程名称：掌握DP-700考试：微软Fabric数据工程师实践 课程概述： 本课程旨在帮助您精准掌握微软DP-700考试（使用微软Fabric实施分析解决方案）。我们的完整模拟考试旨在模拟实际测试的格式、难度和内容，帮助您在首次尝试时成功通过考试。无论您是数据工程师、分析师还是IT专业人士，这些实践测试将提升您的技能并增强信心。DP-700认证，亦称微软认证Fabric数据工程师助理，考试包含40-60道题，时间为120分钟，主要评估您在微软Fabric中数据的摄取、转换、安全性和管理能力。 DP-700考试要点： - 考试代码：DP-700 - 考试时长：120分钟（2小时） - 题目数量：大约40-60道题 - 题型：多项选择题、多重回应题和情境题 - 通过分数：700/1000 - 考试费用：约165美元（视地区而异） - 考试目标：数据的摄取和转换、分析解决方案的安全性和管理、分析解决方案的监控和优化 - 考察技能：在Fabric中设计和实施数据摄取、转换、数据安全及优化技术 - 准备要求：具备微软Fabric的实际操作经验，对数据工程概念的熟悉，以及对考试题型的练习是成功的关键 课程内容： - 真实模拟考试：仿真DP-700考试环境，涵盖100多个涉及各个领域的问题 - 使用微软Fabric设计与实施数据解决方案 - 数据工程、集成与转换 - 监控、优化和安全性 - 基于现实场景的问题 目标受众： 本课程专为希望在微软Fabric数据工程师助理（DP-700）认证中脱颖而出的数据专业人士量身定制。适合参与者包括： - 数据工程师和架构师：有经验于数据提取、转换和加载（ETL）过程的人员，希望深入了解微软Fabric。 - 商业智能专业人士：参与设计和部署数据工程分析解决方案，与分析工程师、架构师、分析师和管理员密切合作的人员。 - 数据分析师和科学家：精通使用SQL、PySpark和Kusto查询语言（KQL）处理和转换数据的专业人员，希望在微软Fabric环境中验证和提升技能。 关键责任： 参与者需具备以下经验： - 数据摄取和转换：实施数据加载模式并转换数据以满足分析需求。 - 分析解决方案管理：确保数据的完整性和性能，对分析解决方案进行安全性、管理、监控和优化。 - 协作：与分析工程师、架构师、分析师和管理员合作，设计和部署全面的数据工程解决方案。 核心能力： - 实施和管理分析解决方案（30-35%）：配置微软Fabric工作区设置（Spark、域、OneLake、数据工作流），实施生命周期管理（版本控制、数据库项目、部署管道），配置安全和治理（访问控制、数据掩码、敏感标签），编排流程（管道、笔记本、调度、触发器）。 - 数据摄取和转换（30-35%）：设计和实施加载模式（全量、增量、流式），为维度建模准备数据，选择合适的数据存储和转换工具（数据流、笔记本、T-SQL），使用PySpark、SQL和KQL摄取和转换批量和流式数据，处理数据质量问题（重复、缺失、延迟到达数据）。 - 监控和优化分析解决方案（30-35%）：监控Fabric项目、数据摄取、转换和语义模型刷新，配置警报并排除错误（管道、数据流、笔记本、事件屋、T-SQL），优化性能（湖屋表、管道、数据仓库、事件流、Spark、查询）。 课程大纲：无
Master the Microsoft DP-700 Exam with PrecisionAre you preparing for the Microsoft DP-700 Exam (Implementing Analytics Solutions Using Microsoft Fabric)? Our full-length practice exams are designed to mirror the actual test's format, difficulty, and content, giving you the edge to pass on your first try. Whether you're a data engineer, analyst, or IT professional, these practice tests will sharpen your skills and boost your confidence.The Microsoft DP-700 certification, also known as the Microsoft Certified Fabric Data Engineer Associate, involves 40-60 questions and a time duration of 120 minutes. The exam assesses your ability to ingest, transform, secure, and manage data within Microsoft Fabric.Key points about the DP-700 exam:Exam Code: DP-700Duration: 120 minutes (2 hours)Number of Questions: Approximately 40-60 questionsQuestion Types: Multiple choice, multiple response, and scenario-based questionsPassing Score: 700/1000Exam Cost: Approximately $165 (USD), but this may vary by regionExam Objectives: Ingesting and transforming data, securing and managing an analytics solution, and monitoring and optimizing an analytics solution.Skills Assessed: Designing and implementing data ingestion, transformation, data security, and optimization techniques within FabricPreparation: Hands-on experience with Microsoft Fabric, familiarity with data engineering concepts, and practice with the exam's question formats are crucial for successWhat's Inside?Realistic Practice ExamsSimulate the actual DP-700 exam environment with 100+ questions covering all domains:Designing & Implementing Data Solutions with Microsoft FabricData Engineering, Integration, and TransformationMonitoring, Optimization, and SecurityReal-World Scenario-Based QuestionsTarget Audience:This course is tailored for data professionals aiming to excel in the Microsoft Fabric Data Engineer Associate (DP-700) certification. Ideal participants include:Data Engineers and Architects: Individuals experienced in data extraction, transformation, and loading (ETL) processes, seeking to deepen their expertise in Microsoft Fabric.Global Knowledge+1Microsoft Learn+1Business Intelligence Professionals: Those involved in designing and deploying data engineering solutions for analytics, collaborating closely with analytics engineers, architects, analysts, and administrators.Data Analysts and Scientists: Professionals proficient in manipulating and transforming data using languages such as Structured Query Language (SQL), PySpark, and Kusto Query Language (KQL), aiming to validate and enhance their skills in a Microsoft Fabric environment.Key Responsibilities:Participants are expected to have experience in:Data Ingestion and Transformation: Implementing data loading patterns and transforming data to meet analytical requirements.Analytics Solution Management: Securing, managing, monitoring, and optimizing analytics solutions to ensure data integrity and performance.Collaboration: Working alongside analytics engineers, architects, analysts, and administrators to design and deploy comprehensive data engineering solutions.Core Competencies:Implement and Manage an Analytics Solution (30-35%):Configure Microsoft Fabric workspace settings (Spark, domain, OneLake, data workflow)Implement lifecycle management (version control, database projects, deployment pipelines)Configure security and governance (access controls, data masking, sensitivity labels)Orchestrate processes (pipelines, notebooks, scheduling, triggers)Ingest and Transform Data (30-35%):Design and implement loading patterns (full, incremental, streaming)Prepare data for dimensional modelingChoose appropriate data stores and transformation tools (dataflows, notebooks, T-SQL)Create and manage data shortcuts and mirroringIngest and transform batch and streaming data using PySpark, SQL, and KQLHandle data quality issues (duplicates, missing, late-arriving data)Monitor and Optimize an Analytics Solution (30-35%):Monitor Fabric items, data ingestion, transformation, and semantic model refreshConfigure alerts and troubleshoot errors (pipelines, dataflows, notebooks, eventhouses, T-SQL)Optimize performance (lakehouse tables, pipelines, data warehouses, eventstreams, Spark, queries)
