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Azure Data Factory Cookbook - Second Edition

You're reading from  Azure Data Factory Cookbook - Second Edition

Product type Book
Published in Feb 2024
Publisher Packt
ISBN-13 9781803246598
Pages 532 pages
Edition 2nd Edition
Languages
Authors (4):
Dmitry Foshin Dmitry Foshin
Profile icon Dmitry Foshin
Tonya Chernyshova Tonya Chernyshova
Profile icon Tonya Chernyshova
Dmitry Anoshin Dmitry Anoshin
Profile icon Dmitry Anoshin
Xenia Ireton Xenia Ireton
Profile icon Xenia Ireton
View More author details

Table of Contents (15) Chapters

Preface Getting Started with ADF Orchestration and Control Flow Setting Up Synapse Analytics Working with Data Lake and Spark Pools Working with Big Data and Databricks Data Migration – Azure Data Factory and Other Cloud Services Extending Azure Data Factory with Logic Apps and Azure Functions Microsoft Fabric and Power BI, Azure ML, and Cognitive Services Managing Deployment Processes with Azure DevOps Monitoring and Troubleshooting Data Pipelines Working with Azure Data Explorer The Best Practices of Working with ADF Other Books You May Enjoy
Index

Introduction to the Azure data platform

The Azure data platform provides us with a number of data services for databases, data storage, and analytics. In Table 1.1, you can find a list of services and their purpose:

Figure 1.1: Azure data platform services

Using Azure data platform services can help you build a modern analytics solution that is secure and scalable. The following diagram shows an example of a typical modern cloud analytics architecture:

Figure 1.2: Modern analytics solution architecture

You can find most of the Azure data platform services here. ADF is a core service for data movement and transformation.

Let’s learn more about the reference architecture in Figure 1.1. It starts with source systems. We can collect data from files, databases, APIs, IoT, and so on. Then, we can use Event Hubs for streaming data and ADF for batch operations. ADF will push data into Azure Data Lake as a staging area, and then we can prepare data for...

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