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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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Using the web activity to call an Azure logic app

Azure Logic Apps allows you to greatly increase the capabilities of ADF. You can use it to send emails to build a notification framework. Countless things that can't be done at this point in time in ADF you can leverage Azure Logic Apps to do.

In this recipe, you will learn how to call an Azure logic app from ADF and how to pass parameters between them to archive files from a folder in Blob storage and delete those files from the original location.

Getting ready

You need to have created an ADF and Azure Data Lake Storage Gen2 account. The Flights dataset (or any other dataset) should be uploaded to Storage. There should be a container called archive created in the Azure Blob storage space. You also need to be familiar with creating ADF pipelines containing the Get Metadata, Filter, and For Each activities. Please refer to Chapter 2, Orchestration and Control Flow, for guidelines on how to do that.

How to do it…...

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