Book Image

Azure Data Factory Cookbook - Second Edition

By : Dmitry Foshin, Tonya Chernyshova, Dmitry Anoshin, Xenia Ireton
4 (1)
Book Image

Azure Data Factory Cookbook - Second Edition

4 (1)
By: Dmitry Foshin, Tonya Chernyshova, Dmitry Anoshin, Xenia Ireton

Overview of this book

This new edition of the Azure Data Factory book, fully updated to reflect ADS V2, will help you get up and running by showing you how to create and execute your first job in ADF. There are updated and new recipes throughout the book based on developments happening in Azure Synapse, Deployment with Azure DevOps, and Azure Purview. The current edition also runs you through Fabric Data Factory, Data Explorer, and some industry-grade best practices with specific chapters on each. You’ll learn how to branch and chain activities, create custom activities, and schedule pipelines, as well as discover the benefits of cloud data warehousing, Azure Synapse Analytics, and Azure Data Lake Gen2 Storage. With practical recipes, you’ll learn how to actively engage with analytical tools from Azure Data Services and leverage your on-premises infrastructure with cloud-native tools to get relevant business insights. You'll familiarize yourself with the common errors that you may encounter while working with ADF and find out the solutions to them. 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 with its latest advancements as the main ETL and orchestration tool for your data warehouse projects.
Table of Contents (15 chapters)
13
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14
Index

Building and orchestrating a data pipeline for Data Lake and Spark

In this recipe, we will explore the process of constructing and orchestrating data pipelines using Data Lake and Spark in Azure Synapse Analytics. By leveraging the capabilities of these services, you can efficiently manage and process large amounts of data for analysis and insights.

We will improve the code in the notebook from the previous recipe to create a data transformation job and orchestrate it from Synapse Integrate. You’ll learn how to extract, transform, and load data into a data lake using Spark, building efficient and scalable pipelines.

Additionally, we’ll cover the crucial aspect of orchestration, where you’ll discover how to schedule, monitor, and manage the execution of your data pipelines using Azure Synapse’s orchestration capabilities.

Getting ready

To get started with the recipe, log in to your Synapse Analytics workspace. You’ll need to have the...