You're reading from Azure Data Engineering Cookbook Get well versed in various data engineering techniques in Azure using this recipe-based guide

Product type Paperback

Published in Sep 2022

Publisher Packt

ISBN-13 9781803246789

Length 608 pages

Edition 2nd Edition

Languages

SQL

Tools

Azure

Concepts

Data Engineering

Authors (3):

Ahmad Osama

Nagaraj Venkatesan

Luca Zanna

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Table of Contents (16) Chapters

Preface

1. Chapter 1: Creating and Managing Data in Azure Data Lake

2. Chapter 2: Securing and Monitoring Data in Azure Data Lake FREE CHAPTER

3. Chapter 3: Building Data Ingestion Pipelines Using Azure Data Factory

4. Chapter 4: Azure Data Factory Integration Runtime

5. Chapter 5: Configuring and Securing Azure SQL Database

6. Chapter 6: Implementing High Availability and Monitoring in Azure SQL Database

7. Chapter 7: Processing Data Using Azure Databricks

8. Chapter 8: Processing Data Using Azure Synapse Analytics

9. Chapter 9: Transforming Data Using Azure Synapse Dataflows

10. Chapter 10: Building the Serving Layer in Azure Synapse SQL Pool

11. Chapter 11: Monitoring Synapse SQL and Spark Pools

12. Chapter 12: Optimizing and Maintaining Synapse SQL and Spark Pools

13. Chapter 13: Monitoring and Maintaining Azure Data Engineering Pipelines

14. Index

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Building Data Ingestion Pipelines Using Azure Data Factory

Azure Data Factory is the data orchestration service in Azure. Using Azure Data Factory, you can build pipelines that are capable of reading data from multiple sources, transforming the data, and loading the data into data stores to be consumed by reporting applications such as Power BI. Azure Data Factory much like SQL Server Integration Services (SSIS) in an on-premises world, provides a code-free UI for developing, managing, and maintaining data engineering pipelines.

Azure Data Factory is the bread and butter for a data engineer and understanding its fundamentals is extremely essential in building efficient pipelines. By the end of the chapter, you will know how to provision a data factory account, copy data from an Azure SQL database to a data lake using copy activity, use control flow activities, move data from SQL Server to a data lake, and choose options to trigger a data factory pipeline.

In this chapter, we...