This course covers comprehensive methods and practices for implementing and managing enterprise-scale data analytics solutions using Microsoft Fabric. Students will build upon existing analytics expertise and develop proficiency in using Microsoft Fabric components, including lakehouses, data warehouses, notebooks, dataflows, data pipelines, and semantic models, to create and deploy robust analytics assets. This course is most appropriately suited for those who have earned the PL-300 certification or possess equivalent expertise in using Power BI for data transformation, modeling, visualization, and sharing across organizations. Additionally, learners should have prior experience in successfully building and deploying data analytics solutions at the enterprise level.
Audience Profile:
The primary audience for this course consists of data professionals with extensive experience in data modeling, extraction, and analytics. This course is specifically designed for professionals who want to leverage Microsoft Fabric to create and deploy enterprise-scale data analytics solutions that drive business value.
Course Outline:
- Introduction to end-to-end analytics using Microsoft Fabric (6 Units)
- Administer Microsoft Fabric (7 Units)
- Ingest Data with Dataflows Gen2 in Microsoft Fabric (7 Units)
- Ingest data with Spark and Microsoft Fabric notebooks (7 Units)
- Use Data Factory pipelines in Microsoft Fabric (8 Units)
- Get started with lakehouses in Microsoft Fabric (7 Units)
- Organize a Fabric lakehouse using medallion architecture design (8 Units)
- Use Apache Spark in Microsoft Fabric (9 Units)
- Work with Delta Lake tables in Microsoft Fabric (8 Units)
- Get started with data warehouses in Microsoft Fabric (9 Units)
- Load data into a Microsoft Fabric data warehouse (8 Units)
- Query a data warehouse in Microsoft Fabric (7 Units)
- Monitor a Microsoft Fabric data warehouse (7 Units)
- Understand scalability in Power BI (7 Units)
- Create Power BI model relationships (8 Units)
- Use tools to optimize Power BI performance (7 Units)
- Enforce Power BI model security (7 Units)
