Modern organizations rely on dependable data workflows to move and transform information across cloud services. This text-based course introduces you to cloud data integration using Azure Data Factory, guiding you through core ETL concepts and practical pipeline development step by step.
You will begin with essential cloud storage concepts, terminology, and architecture before learning how to design automated data movement routines. By reading through structured explanations and analyzing real-world configuration examples, you will develop the foundational skills needed to orchestrate data flows with confidence.
What you'll learn:
- Understand fundamental data integration concepts, linked services, datasets, and pipeline structures
- Configure automated data ingestion pipelines to move data between diverse cloud data stores
- Build transformation workflows using mapping data flows without writing low-level code
- Implement triggers for scheduled, tumbling window, and event-driven data processing
- Apply pipeline parameterization and modern secrets management practices for secure deployments
- Monitor pipeline execution runs, inspect debug logs, and handle runtime errors effectively
The course starts with essential terminology and the cloud data landscape, progressing smoothly into pipeline design, data transformation, and operational management. This course is designed for beginners in data engineering and cloud integration, requiring no prior experience with Azure Data Factory. Read at your own pace and start building robust cloud data pipelines today.
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