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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Index

Ingest data into Delta Lake using Mapping Data Flows

Delta Lake is a cutting-edge open source storage layer that ensures the atomicity, consistency, isolation, and durability of data within a lake. Essentially, Delta Lake conforms to ACID standards, making it an ideal solution for data management. In addition to offering scalable metadata handling and support for ACID transactions, Delta Lake integrates seamlessly with existing Data Lakes and Apache Spark APIs. If you're interested in exploring Delta Lake, there are several options available to you. Databricks provides notebooks, along with compatible Apache Spark APIs, to create and manage Delta Lakes. On the other hand, Azure Data Factory's Mapping Data Flows allow for ACID-compliant CRUD operations through simplified ETL pipelines using scaled-out Apache Spark clusters. This recipe will walk you through how to get started with Delta Lake using Azure Data Factory's new Delta Lake connector, demonstrating how to create...