Microsoft Fabric Data Engineer (Cloud Share)
This course covers methods and practices for implementing and managing enterprise-scale data analytics solutions using Microsoft Fabric. Students will learn how to use Fabric dataflows, pipelines, and notebooks to develop analytics assets such as semantic models, data warehouses, and lakehouses. This course is designed for experienced data professionals skilled at data preparation, modeling, analysis, and visualization, such as the PL-300: Power BI Data Analyst certification.
What's Included:
- 10 launches per module
- Free Access to production Azure Subscription (No sign up / credit cards)
- Free 24/7 premier support
- Free instructor access
Platform Features:
- Seamless paste to virtual machine functionality
- Integrated keyboard language translation for all countries
- Integrated step-by-step instructions
- Remote classroom management for instructors & admins
- Student progress reporting
- MS Learn content integration
| Lab | Estimated completion time |
|---|---|
| 1. Create a Microsoft Fabric Lakehouse |
60 mins
|
| 2. Analyze data with Apache Spark |
60 mins
|
| 3. Use Delta Tables in Apache Spark |
90 mins
|
| 4. Create and use Dataflows (Gen2) in Microsoft Fabric |
60 mins
|
| 5. Ingest data with a pipeline in Microsoft Fabric |
60 mins
|
| 6. Create a medallion architecture in a Microsoft Fabric lakehouse |
120 mins
|
| 7. Get started with Real-Time Intelligence in Microsoft Fabric |
60 mins
|
| 8. Ingest real-time data with Eventstream in Microsoft Fabric |
60 mins
|
| 9. Work with data in a Microsoft Fabric eventhouse |
60 mins
|
| 10. Analyze data in a data warehouse |
60 mins
|
| 11. Load data into a warehouse using T-SQL |
60 mins
|
| 12. Monitor a data warehouse in Microsoft Fabric |
60 mins
|
| 13. Secure a Microsoft Fabric data warehouse |
90 mins
|
| 14. Implement deployment pipelines in Microsoft Fabric |
60 mins
|
| 15. Monitor Fabric activity in the monitoring hub |
60 mins
|
| 16. Secure data access in Microsoft Fabric (Requires 2 Users) |
90 mins
|
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