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所在平台: Udemy |
课程主页: https://www.udemy.com/course/azure-data-engineer-interview-mastery-600-most-asked-qa/
课程评论：没有评论
课程名称：Azure 数据工程师面试精通：600+ 最常见问题与解答 概述：您是否在为2025年的关键Azure数据工程师面试做准备？本课程提供了一套经过严格筛选的600多个基于场景的问题，涵盖Microsoft最新的架构标准、Fabric生态系统和DP-700的期望。您将不仅仅停留在传统的选择题上，而是深入真实的案例研究、长篇场景和现代数据栈中的细微权衡。该课程旨在为在职专业人员、换工作者和跨国公司面试候选人提供，融合了云原生思维与实践数据工程策略，理想于掌握大科技公司的面试。 每个问题都包含： - 清晰的场景叙述与现实企业用例 - 四个经过深思熟虑的答案选项，具有考试级别的深度 - 详细解释，分解概念、背景以及为何正确选项最优 学习目标： 通过本课程，您将在以下领域获得自信： - Microsoft Fabric 面试问题（以DP-700为导向） - Azure Synapse、Data Factory和OneLake的整合 - Databricks、Spark、Delta Lake和无服务器SQL的性能决策 - CI/CD管道、基础设施即代码（IaC）和治理政策 - 现代Azure部署中的监控、可观察性和FinOps权衡 课程大纲 - 涵盖主题： 1. 云与数据工程基础 - Azure资源组、虚拟网络、ARM与Bicep - SQL查询设计、Python用于ETL、Docker和Git管道 - 数据架构原则：ACID、BASE、Lambda、Kappa - 从经典Synapse过渡到Fabric优先的OneLake分析 2. Azure上的存储与数据管理 - Azure Data Lake Storage Gen2、生命周期策略 - Azure SQL等级、内存OLTP、Synapse专用池 - Cosmos DB APIs和全球一致性决策 - Fabric湖仓与数据仓库自动化策略 3. 数据摄取、集成与编排 - Azure Data Factory与Synapse管道的最佳用例 - 使用事件中心、物联网中心实时数据摄取 - SQL CDC和Debezium在AKS上的变更数据捕获 - 使用数据激活器和Dataflows Gen 2的触发式自动化 - 从SSIS迁移到Azure本地编排 4. 处理与分析引擎 - Databricks Spark内部、Photon引擎、Unity Catalog - 无服务器SQL调优与成本优化 - Fabric笔记本和基于Copilot的分析工作流 - 使用Azure Stream Analytics和Power BI进行实时流处理 - 深入查询性能、Z-ordering、缓存和索引 5. 治理、安全与合规 - 基于Azure AD的角色权限管理、托管标识和云安全防护 - 加密层次：传输中、静态、ADE、TDE - 使用Microsoft Purview扫描、分类和标记敏感数据 - 网络架构：私有端点、防火墙、VNet集成 - 通过Azure Policy和Purview自动化GDPR/PCI-DSS合规性 6. 可观察性、优化与数据运维 - Azure Monitor、日志分析和Fabric特定监控视图 - Spot定价、工作负载隔离和Fabric中的容量调优 - 测试框架：Great Expectations、SQL单元测试 - Terraform、Bicep、GitHub Actions：真实世界的IaC和CI/CD策略 - 事件管理、警报工作流和自动化修复
Are you preparing for a career-defining Azure Data Engineer interview in 2025? This course delivers a rigorously curated and exam-ready bank of 600+ scenario-based questions built on Microsoft's latest architecture standards, Fabric ecosystem, and DP-700 expectations.You'll go beyond shallow MCQs and dive into real-world practical case studies, long-form scenarios, and nuanced trade-offs across the modern data stack.Designed for working professionals, job switchers, and MNC interview candidates, this course blends cloud-native thinking with hands-on data engineering strategy-ideal for mastering interviews at Big tech companiesEach question includes:Clear scenario narrative with a realistic enterprise use caseFour carefully balanced answer options with exam-like depthDetailed explanations breaking down concepts, context, and why the correct option works best What You'll LearnBy the end of this course, you'll confidently handle:Microsoft Fabric interview questions (DP-700 oriented)Azure Synapse, Data Factory, and OneLake integrationsDatabricks, Spark, Delta Lake, and Serverless SQL performance decisionsCI/CD pipelines, infrastructure as code (IaC), and governance policiesMonitoring, observability, and FinOps trade-offs across modern Azure deployments Course Syllabus - Topics Covered1 · Cloud & Data Engineering FoundationsAzure Resource Groups, Virtual Networks, ARM vs BicepSQL query design, Python for ETL, Docker & Git for pipelinesData architecture principles: ACID, BASE, Lambda, KappaTransitioning from classic Synapse to Fabric-first OneLake analytics2 · Storage & Data Management on AzureAzure Data Lake Storage Gen2, lifecycle policiesAzure SQL tiers, In-Memory OLTP, Synapse Dedicated PoolsCosmos DB APIs and global consistency decisionsFabric Lakehouse and Warehouse automation strategies3 · Ingestion, Integration & OrchestrationAzure Data Factory vs Synapse Pipelines: Best use casesReal-time data ingestion using Event Hubs, IoT HubChange Data Capture via SQL CDC and Debezium on AKSTrigger-based automation with Data Activator and Dataflows Gen 2Migrating from SSIS to Azure-native orchestration4 · Processing & Analytics EnginesDatabricks Spark internals, Photon engine, Unity CatalogServerless SQL tuning and cost optimizationFabric Notebooks and Copilot-based analytics workflowsReal-time streaming with Azure Stream Analytics and Power BIDeep dive into query performance, Z-ordering, caching, and indexing5 · Governance, Security & ComplianceAzure AD-based RBAC, Managed Identities, and Defender for CloudEncryption layers: in-transit, at-rest, ADE, TDEMicrosoft Purview for scanning, classifying, labeling sensitive dataNetwork architecture: private endpoints, firewalls, VNet integrationAutomating GDPR/PCI-DSS compliance via Azure Policy & Purview6 · Observability, Optimization & DataOpsAzure Monitor, Log Analytics, and Fabric-specific monitoring viewsSpot pricing, workload isolation, and capacity tuning in FabricTesting frameworks: Great Expectations, SQL unit testsTerraform, Bicep, GitHub Actions: Real-world IaC and CI/CD strategiesIncident management, alerting workflows, and automated remediation
