Build practical expertise in designing, managing, and optimizing data pipelines with Microsoft Azure Data Factory (ADF). Across four progressive modules, you’ll move from foundational setup to advanced data integration by configuring ADF, Azure Blob Storage, SQL schemas, source and sink datasets, and copy activities.

Designed for data professionals, data engineers, and cloud practitioners, this hands-on course guides you through building, debugging, deploying, and scheduling end-to-end pipelines. You’ll automate workflow execution with triggers, monitor pipeline runs and performance metrics, interpret execution logs, and diagnose failures using ADF monitoring and diagnostic features. You’ll also integrate Azure Data Lake, create dynamic datasets, parameterize pipelines, and validate inputs to support scalable, reliable workflows. Interactive exercises, scenario-based activities, and graded assessments reinforce each stage of the learning process. By the end of the course, you’ll be able to construct production-ready data pipelines, automate execution, assess data integrity, troubleshoot pipeline issues, and optimize cloud data integration processes. Whether you’re creating your first ADF pipeline or strengthening existing Azure skills, this course offers a structured path from setup through advanced pipeline optimization.