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

External integrations with other compute engines (Snowflake)

Azure Data Factory (ADF), a powerful cloud-based data integration service from Microsoft, has emerged as the go-to solution for enterprises seeking efficient and scalable data movement across various platforms. With its extensive capabilities, ADF not only enables seamless data integration within the Azure ecosystem but also offers external integrations with leading compute engines such as Snowflake.

Azure Data Factory’s integration with Snowflake enables enterprises to seamlessly leverage cloud data warehousing capabilities. Snowflake’s architecture, built for the cloud, complements Azure’s cloud-native approach, offering a scalable and elastic solution for storing and processing vast amounts of data. The integration supports the creation of cost-effective and scalable data solutions. Azure Data Factory’s ability to dynamically manage resources and Snowflake’s virtual warehouse architecture...