Fabric Foundations and Environment Management
About this course
This course introduces the core concepts, architecture, and workflows that define modern data engineering using Microsoft Fabric. Learners develop a working understanding of how data engineers ingest, organize, transform, and prepare data so it can support analytics, reporting, and AI workloads. The course focuses on the early stages of the data engineering lifecycle: understanding Fabric architecture, working with Lakehouses, ingesting data from multiple sources, and preparing structured datasets that support downstream analytics. Rather than treating Fabric tools as isolated features, the course emphasizes how these tools work together within a unified data platform. Learners explore how data engineers move data from raw ingestion to structured, analytics-ready datasets while maintaining reliability, scalability, and data quality. By the end of the course, learners understand how Fabric’s Lakehouse architecture, Dataflows Gen2, and integration workflows support end-to-end data engineering pipelines.
75/100
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What you'll learn
- understand Fabric architecture
- work with Lakehouses
- ingest data from multiple sources
- prepare structured datasets for analytics
- maintain data reliability and quality
Course objectives
- develop a working understanding of data engineering workflows
- learn to manage data ingestion and transformation
- explore integration workflows within Microsoft Fabric
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