This course is designed to build your foundational skills in data engineering on Microsoft Fabric, focusing on the Lakehouse concept. This course will explore the powerful capabilities of Apache Spark for distributed data processing and the essential techniques for efficient data management, versioning, and reliability by working with Delta Lake tables. This course will also explore data ingestion and orchestration using Dataflows Gen2 and Data Factory pipelines. This course includes a combination of lectures and hands-on exercises that will prepare you to work with lakehouses in Microsoft Fabric.
The primary audience for this course is data professionals who are familiar with data modeling, extraction, and analytics. It is designed for professionals who are interested in gaining knowledge about Lakehouse architecture, the Microsoft Fabric platform, and how to enable end-to-end analytics using these technologies.
Job role: Data Analyst, Data Engineer, Data Scientist
You should be familiar with basic data concepts and terminology.
Introduction to end-to-end analytics using Microsoft Fabric
Discover how Microsoft Fabric can meet your enterprise's analytics needs in one platform. Learn about Microsoft Fabric, how it works, and identify how you can use it for your analytics needs.
Get started with lakehouses in Microsoft Fabric
In this module, you'll learn how to:
Use Apache Spark in Microsoft Fabric
In this module, you'll learn how to:
Work with Delta Lake tables in Microsoft Fabric
In this module, you'll learn how to:
Ingest Data with Dataflows Gen2 in Microsoft Fabric
In this module, you'll learn how to:
