Implementing Data Engineering Solutions - Microsoft Fabric

About this course

As a candidate for this exam, you should have subject matter expertise with data loading patterns, data architectures, and orchestration processes. Your responsibilities for this role include:Ingesting and transforming data.Securing and managing an analytics solution.Monitoring and optimizing an analytics solution.You work closely with analytics engineers, architects, analysts, and administrators to design and deploy data engineering solutions for analytics.You should be skilled at manipulating and transforming data by using Structured Query Language (SQL), PySpark, and Kusto Query Language (KQL).Skills at a glanceImplement and manage an analytics solution (30–35%)Ingest and transform data (30–35%)Monitor and optimize an analytics solution (30–35%)Implement and manage an analytics solution (30–35%)Configure Microsoft Fabric workspace settingsConfigure Spark workspace settingsConfigure domain workspace settingsConfigure OneLake workspace settingsConfigure Dataflows Gen2 workspace settingsImplement lifecycle management in FabricConfigure version controlImplement database projectsCreate and configure deployment pipelinesConfigure security and governanceImplement workspace-level access controlsImplement item-level access controlsImplement row-level, column-level, object-level, and folder/file-level access controlsImplement dynamic data maskingApply sensitivity labels to itemsEndorse itemsImplement and use Microsoft Fabric audit logsConfigure and implement OneLake securityOrchestrate processes</

Course objectives

• Understand data loading patterns and architectures
• Collaborate effectively with analytics teams
• Utilize Structured Query Language (SQL), PySpark, and Kusto Query Language (KQL)