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Course Outline
Module 1 – Introduction to Microsoft Fabric
- Platform overview and component breakdown
- Integration with Microsoft 365 and other Microsoft services
- Key distinctions 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: merging Data Lake and 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
- A solid understanding of fundamental data concepts and cloud services
- Practical experience with data analytics tools such as Power BI or SQL
- Familiarity with Microsoft 365 environments
Target Audience
- Data analysts and engineers
- Business intelligence developers
- IT professionals specializing in Microsoft data platforms
21 Hours