Fabric Data Ingestion and Transformation for Beginners

Modern data analytics relies on the ability to efficiently collect, clean, and consolidate information from various sources. This text-based course guides you through the foundational concepts of Fabric, enabling you to build scalable data pipelines and shape your data for analysis. You will progress from understanding basic data warehousing concepts to implementing structured data ingestion workflows. By reading through clear, step-by-step explanations and analyzing structured code snippets, you will gain the confidence to design and manage data pipelines, work with lakehouses, and transform raw data into valuable business insights. What you'll learn: 1. Understand the core architecture of Fabric and the Medallion data framework. 2. Ingest data from diverse sources using data pipelines and dataflows. 3. Transform and clean raw data using Spark notebooks and SQL queries. 4. Configure Delta Lake tables to optimize storage and query performance. 5. Apply best practices for data orchestration and workflow automation. 6. Practice building end-to-end data integration paths through written exercises. The course begins with foundational terminology, defining the core components of modern data estates and Fabric environments. You will then explore step-by-step written guides on configuring connections, writing transformation logic, and orchestrating automated data runs. This course is designed for aspiring data engineers, database administrators, and business analysts who are new to Fabric. No prior experience with data engineering platforms is required, though a basic understanding of data concepts is helpful. Start your journey toward mastering modern data integration today.