This course helps you master Azure Data Factory, build scalable pipelines, integrate data, orchestrate workflows, and excel in data engineering roles.

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Azure has become a leading cloud platform. Expertise in ADF opens doors to lucrative roles in data engineering and analytics.

This course provides you with the essential skills to master Azure Data Factory. You’ll start with ADF’s core concepts, architecture, and data connectivity to both on-premises and cloud sources. Through hands-on lessons and real-world examples, you’ll learn to create, manage, and monitor pipelines, handle incremental data loads, and work with version control using Git. Advanced topics include big data integration with Azure SQL, HDInsight, and Hive and designing analytics and machine learning workflows.

After completing this course, you’ll confidently design, develop, and maintain data pipelines in Azure Data Factory. You’ll be equipped to tackle integration challenges, optimize cost and performance, ensure scalability and high availability, and implement data governance and security—boosting your career prospects in data engineering and analytics.

Azure Data Factory Bootcamp: From Beginner to Expert

Learn how to create Azure Data Factory instances using the portal and Azure CLI.

Creating an Azure Data Factory Instance

Getting Started

Introduction to Azure Data Factory

Setting Up an Azure Data Factory Environment

Data Connectivity and Management

Azure Data Factory: Introduction and Connectivity Exam

Creating Data Pipelines in Azure Data Factory

Managing and Monitoring Azure Data Factory Pipelines

Azure Data Factory: Designing and Maintaining Data Pipelines Exam

Big Data Integration and Processing

Machine Learning and Advanced Analytics

Azure Data Factory: Big Data Processing and Machine Learning Exam

Data Governance and Security

Azure Data Factory: Best Practices

Conclusion

Appendix

Creating an Azure Data Factory Instance

Creating an ADF instance through Azure portal UI