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Artículo: AMZ-B0DQ2FNQ8M
Exam DP-700 Certification Guide: Data Engineering Solutions with Microsoft Fabric: Prepare for Microsoft DP 700 Exam Ref with Real-World Questions, Answers, ... Preparation Series (Unofficial))
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- Prepare for the Microsoft DP-700 exam with our comprehensive guide to Data Engineering Solutions using Microsoft Fabric. This book is your ultimate resource to pass the DP 700 Microsoft certification exam, designed for data engineers looking to level up their skills and boost their careers.Table of ContentsChapter 1: Introduction to Microsoft FabricIntroduction to DP-700Overview of Microsoft FabricKey components of Microsoft FabricPrerequisites for the DP-700 ExamPreparing for the ExamCareer and Job OpportunitiesChapter 2: Planning and Designing Data Engineering SolutionsMedallion architecture principlesData modeling best practicesChoosing appropriate data storage solutions (e.g., Azure Data Lake, Delta Lake)Real-time vs. batch data processing considerationsChapter 3: Implementing Data IngestionBatch data ingestion using pipelines and dataflowsStreaming data ingestion using EventStream and Spark Structured StreamingHandling different ingestion patterns: full load, incremental load, and mirroringData quality and duplication managementChapter 4: Transforming Data in Microsoft FabricData transformation tools: PySpark, T-SQL, and KQLDelta Lake API: Optimizations, VACUUM, and V-OrderDenormalization and aggregation techniquesHandling late-arriving and missing dataChapter 5: Orchestrating Data PipelinesCreating pipelines with triggers and schedulesOrchestration with notebooks and parameterized workflowsIntegration of pipelines with Git for version controlDynamic data flow patternsError handling and debugging in pipelinesChapter 6: Securing Data SolutionsWorkspace and item-level access controlsRow-level, column-level, and object-level securityDynamic data maskingSensitivity labels and data governance practicesChapter 7: Real-Time IntelligenceProcessing and querying real-time dataImplementing windowing functionsMonitoring real-time data flows with EventStream and KQLBuilding and optimizing real-time analytics solutionsChapter 8: Monitoring and Optimizing Data SolutionsMonitoring data pipelines and transformationsResolving errors in pipelines, dataflows, and notebooksPerformance optimization for data ingestion and transformationsConfiguring alerts and real-time monitoringChapter 9: Deploying and Managing SolutionsUsing deployment pipelines in Microsoft FabricMulti-environment deployment strategiesManaging semantic models and data warehousesBest practices for deployment and scalingChapter 10: Practice Questions and Exam PreparationPractice MCQs with detailed explanationsCase-study-based scenariosTips for exam successKey Features of This Book:Planning and Designing Data SolutionsBatch and Streaming Data IngestionData TransformationSecuring DataReal-Time AnalyticsExam Preparation
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