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Azure Data Engineering Cookbook

You're reading from   Azure Data Engineering Cookbook Design and implement batch and streaming analytics using Azure Cloud Services

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Product type Paperback
Published in Apr 2021
Publisher Packt
ISBN-13 9781800206557
Length 454 pages
Edition 1st Edition
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Authors (2):
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Nagaraj Venkatesan Nagaraj Venkatesan
Author Profile Icon Nagaraj Venkatesan
Nagaraj Venkatesan
Ahmad Osama Ahmad Osama
Author Profile Icon Ahmad Osama
Ahmad Osama
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Toc

Table of Contents (11) Chapters Close

Preface 1. Chapter 1: Working with Azure Blob Storage 2. Chapter 2: Working with Relational Databases in Azure FREE CHAPTER 3. Chapter 3: Analyzing Data with Azure Synapse Analytics 4. Chapter 4: Control Flow Activities in Azure Data Factory 5. Chapter 5: Control Flow Transformation and the Copy Data Activity in Azure Data Factory 6. Chapter 6: Data Flows in Azure Data Factory 7. Chapter 7: Azure Data Factory Integration Runtime 8. Chapter 8: Deploying Azure Data Factory Pipelines 9. Chapter 9: Batch and Streaming Data Processing with Azure Databricks 10. Other Books You May Enjoy

Chapter 4: Control Flow Activities in Azure Data Factory

Azure Data Factory (ADF) is a cloud extract, transform, and load service. ADF is used to read data from multiple sources, transforming and loading the data into databases to be consumed for reporting, data science, or machine learning. ADF provides a code-free UI to develop, manage, and maintain data pipelines.

ADF is compatible with SQL Server Integration Services (SSIS). Existing SSIS packages can be easily migrated and run in ADF.

ADF is an essential Azure data engineering product and is a must for an Azure data engineer to learn.

In this chapter, we'll cover the following recipes:

  • Implementing control flow activities
  • Implementing control flow activities – Lookup and If activities
  • Triggering a pipeline in Azure Data Factory
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