Modern Data Integration Made Easy with Azure Data Factory.
Key Features
? Learn everything from provisioning to building robust, interactive pipelines using ADF Studio.
? Apply Azure Data Factory to real-life data challenges and business use cases with confidence.
? Master optimization, security, CI/CD integration, and production-grade deployment in modern data pipelines.
Book Description
Azure Data Factory (ADF) enables seamless orchestration, transformation, and movement of data across hybrid and cloud environments—making it a key skill for modern data professionals. Mastering Azure Data Factory for Modern Data Integration is a comprehensive guide to Microsoft’s powerful cloud-based data integration service.
This book, crafted by industry experts, walks you through every stage of ADF implementation—from provisioning and building robust pipelines to handling complex workflows, securing data, and optimizing performance. This book takes you on a practical journey, starting with the foundational concepts of ADF, helping you understand its architecture, core components, and user-friendly interface. You’ll learn how to create and manage pipelines, move and transform data, and orchestrate complex workflows using real-world data scenarios. As you progress, the book delves into advanced topics like performance optimization, security best practices, and integration with Azure Fabric, ensuring you're ready to tackle enterprise-grade challenges.
By the end of this hands-on guide, you’ll have transitioned from simply using ADF to mastering it—confidently designing, deploying, and scaling data integration solutions tailored to your organization’s needs. Whether you're just starting your cloud data journey or aiming to elevate your expertise, this book ensures you don’t get left behind in the data-driven future.
What you will learn
? Design and orchestrate ETL pipelines using Azure Data Factory.
? Provision and configure ADF and linked services via Azure Portal.
? Understand ADF architecture, components, and integration capabilities.
? Build scalable data pipelines for movement and transformation.
? Implement security, compliance, and access control best practices.
? Deploy, monitor, optimize, and troubleshoot production-grade pipelines.
Table of Contents
1. Introduction to Azure Data Factory
2. Core Concepts and Architecture
3. Creating and Managing Pipelines
4. Data Movement and Transformation
5. Orchestrating Complex Workflows
6. Data Ingestion Patterns
7. Security and Compliance
8. Performance Tuning and Optimization
9. Advanced Features and Use Cases
10. Troubleshooting and Debugging
11. Fabric and Azure Data Factory
Index
About the Authors
Ashish Agarwal is currently working as Senior Engineering Architect in Azure SQL Engineering team at Microsoft, where he works on large and complex SQL modernization projects, transitioning from SQL on-premises to Azure IaaS and PaaS Platforms.
Narendra Ragho Angane is a Principal Engineering Architect Manager for the SQL CSE/Ninja Team at Microsoft Engineering, specializing in the SQL Server family and Azure Data Services.
Vijay Kumar is a Senior Engineering Architect in the Azure SQL Engineering team at Microsoft. He oversees modernization initiatives for both heterogeneous and homogeneous environments. His work involves migrating SQL Server, Oracle, PostgreSQL, and MySQL workloads from on-premises systems to Azure IaaS and PaaS platforms, assisting enterprise customers with the transition to cloud-native data solutions.
