Microsoft Fabric exercises
The following exercises are designed to support the modules on Microsoft Learn.
| Module | Lab |
|---|---|
| Get started with lakehouses in Microsoft Fabric | Create a Microsoft Fabric Lakehouse |
| Use Apache Spark to work with files in a lakehouse | Analyze data with Apache Spark |
| Work with Delta Lake tables in Microsoft Fabric | Use delta tables in Apache Spark |
| Organize a Fabric lakehouse using medallion architecture design | Create a medallion architecture in a Microsoft Fabric lakehouse |
| Use Data Factory pipelines in Microsoft Fabric | Ingest data with a pipeline in Microsoft Fabric |
| Ingest Data with Dataflows Gen2 in Microsoft Fabric | Create and use Dataflows (Gen2) in Microsoft Fabric |
| Get started with data warehouses in Microsoft Fabric | Analyze data in a data warehouse |
| Load data into a warehouse in Microsoft Fabric | Load data into a warehouse using T-SQL |
| Query a data warehouse in Microsoft Fabric | Query a data warehouse in Microsoft Fabric |
| Monitor a data warehouse in Microsoft Fabric | Monitor a data warehouse in Microsoft Fabric |
| Secure a Microsoft Fabric data warehouse | Secure a Microsoft Fabric data warehouse |
| Get started with Real-Time Intelligence in Microsoft Fabric | Get started with Real-Time Intelligence in Microsoft Fabric |
| Get started with data science in Microsoft Fabric | Get started with data science in Microsoft Fabric |
| Explore data for data science with notebooks in Microsoft Fabric | Explore data for data science with notebooks in Microsoft Fabric |
| Preprocess data with Data Wrangler in Microsoft Fabric | Preprocess data with Data Wrangler in Microsoft Fabric |
| Train and track machine learning models with MLflow in Microsoft Fabric | Train and track machine learning models with MLflow in Microsoft Fabric |
| Generate batch predictions using a deployed model in Microsoft Fabric | Generate batch predictions using a deployed model in Microsoft Fabric |
| Ingest real-time data with Eventstream in Microsoft Fabric | Ingest real-time data with Eventstream in Microsoft Fabric |
| Ingest data with Spark and Microsoft Fabric notebooks | Ingest data with Spark and Microsoft Fabric notebooks |
| Work with data in a Microsoft Fabric eventhouse | Work with data in a Microsoft Fabric eventhouse |
| Get started with Real-Time Dashboards in Microsoft Fabric | Get started with Real-time Dashboards in Microsoft Fabric |
| Understand scalability in Power BI | Create and explore a semantic model |
| Create DAX calculations in Power BI Desktop | Create DAX calculations in Power BI Desktop |
| Design scalable semantic models | Design scalable semantic models |
| Design and build tabular models | Work with model relationships |
| Create reusable Power BI assets | Create reusable Power BI assets |
| Optimize enterprise-scale tabular models | Use tools to optimize Power BI performance |
| Design and build tabular models | Enforce semantic model security |
| Monitoring Fabric | Monitor Fabric activity in the monitoring hub |
| Secure data access in Microsoft Fabric | Secure data access in Microsoft Fabric |
| Get started with SQL Database in Microsoft Fabric | Work with SQL Database in Microsoft Fabric |
| Get started with GraphQL in Microsoft Fabric | Work with API for GraphQL in Microsoft Fabric |
| Implement CI/CD in Microsoft Fabric | Implement deployment pipelines in Microsoft Fabric |