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Azure Data Factory Cookbook

Azure Data Factory Cookbook

By : Dmitry Anoshin, Dmitry Foshin, Storchak, Xenia Ireton
4.2 (13)
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Azure Data Factory Cookbook

Azure Data Factory Cookbook

4.2 (13)
By: Dmitry Anoshin, Dmitry Foshin, Storchak, Xenia Ireton

Overview of this book

Azure Data Factory (ADF) is a modern data integration tool available on Microsoft Azure. This Azure Data Factory Cookbook helps you get up and running by showing you how to create and execute your first job in ADF. You’ll learn how to branch and chain activities, create custom activities, and schedule pipelines. This book will help you to discover the benefits of cloud data warehousing, Azure Synapse Analytics, and Azure Data Lake Gen2 Storage, which are frequently used for big data analytics. With practical recipes, you’ll learn how to actively engage with analytical tools from Azure Data Services and leverage your on-premise infrastructure with cloud-native tools to get relevant business insights. As you advance, you’ll be able to integrate the most commonly used Azure Services into ADF and understand how Azure services can be useful in designing ETL pipelines. The book will take you through the common errors that you may encounter while working with ADF and show you how to use the Azure portal to monitor pipelines. You’ll also understand error messages and resolve problems in connectors and data flows with the debugging capabilities of ADF. By the end of this book, you’ll be able to use ADF as the main ETL and orchestration tool for your data warehouse or data platform projects.
Table of Contents (12 chapters)
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Chapter 2: Orchestration and Control Flow

Azure Data Factory is an excellent tool for designing and orchestrating your Extract, Transform, Load (ETL) processes. In this chapter, we introduce several fundamental data factory concepts and guide you through the creation and scheduling of increasingly complex data-driven workflows. All the work in this chapter is done using the Microsoft data factory online portal. You'll learn how to create and configure Linked Services and datasets, take advantage of built-in expressions and functions, and, most importantly, learn how and when to use the most popular Data Factory activities.

This chapter covers the following topics:

  • Using parameters and built-in functions
  • Using the Metadata and Stored Procedure activities
  • Using the ForEach and Filter activities
  • Chaining and branching activities within a pipeline
  • Using the Lookup, Web, and Execute Pipeline activities
  • Creating event-based pipeline triggers

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