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

Working with Azure Data Explorer

In this chapter, we delve into two key services within the Azure Data platform: Azure Data Factory (ADF) and Azure Data Explorer (ADX). ADX is a fast and highly scalable data exploration service for log and telemetry data offered by Microsoft Azure. It provides real-time analysis capabilities, helping organizations to rapidly ingest, store, analyze, and visualize vast amounts of data. The use cases for ADX span across a range of sectors and applications, from IoT solutions to user behavior analytics and application monitoring, all with the goal of turning raw data into actionable insights.

In the context of ADX, ADF can be used to automate the process of data ingestion from various sources into ADX, perform the necessary transformations, and manage data workflows.

We will cover the following recipes:

  • An introduction to ADX, its architecture, and key features
  • Overview of common use cases for ADX and ADF
  • Setting up a data...