Course Outline

Module 1 – Introduction to Microsoft Fabric

  • Overview of the platform and its components
  • Integration with Microsoft 365 and other Microsoft services
  • Differences between Data Factory, Synapse, and Fabric

Module 2 – Creating and Managing Workspaces

  • Understanding Fabric Workspaces
  • Creating and organizing Workspaces
  • Permissions and access management

Module 3 – Lakehouse in Fabric

  • Lakehouse concept: combining Data Lake + Data Warehouse
  • Creating a Lakehouse in Fabric
  • Importing and managing data

Module 4 – Notebooks in Fabric

  • Introduction to Notebooks (Python, SQL)
  • Creating and running notebooks within Fabric
  • Use cases for exploratory analysis and data transformations

Module 5 – Pipelines (Visual ETL)

  • ETL concepts in Microsoft Fabric
  • Creating visual pipelines for data ingestion and transformation
  • Scheduling and monitoring data flows

Module 6 – Data Warehouse

  • Creating Data Warehouses in Fabric
  • Table modeling and relationships
  • Integrating with other data sources and layers

Module 7 – Semantic Model

  • What is a semantic model and why it matters
  • Creating and editing analytical models
  • Measures, hierarchies, and KPIs

Module 8 – Building Reports in Power BI

  • Connecting to the semantic model
  • Best practices in dashboard design
  • Sharing and publishing reports in Fabric

Summary and Next Steps

Requirements

  • An understanding of core data concepts and cloud services
  • Experience with data analytics tools such as Power BI or SQL
  • Familiarity with Microsoft 365 environments

Audience

  • Data analysts and engineers
  • Business intelligence developers
  • IT professionals working on Microsoft data platforms
 21 Hours

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