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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
Languages
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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

What this book covers

Chapter 1, Working with Azure Blob Storage, covers how to work with Azure Blob storage and understand how it is used when orchestrating a data workflow.

Chapter 2, Working with Relational Databases in Azure, explains how to provision and work with Azure SQL Database.

Chapter 3, Analyzing Data with Azure Synapse Analytics, describes how to provision an Azure Synapse database and ingest and analyze data in Azure Synapse.

Chapter 4, Control Flow Activities in Azure Data Factory, explains how to implement different control activities available in Azure Data Factory.

Chapter 5, Control Flow Transformation and the Copy Data Activity in Azure Data Factory, explains how to work with the Azure Data Factory integration runtime. You'll also learn to use the SSIS package with Azure Data Factory.

Chapter 6, Data Flow in Azure Data Factory, explains how to use Azure Data Factory mapping and wrangling data flow to extract, transform, and load data.

Chapter 7, Azure Data Factory Integration Runtime, details the different integration runtimes available and their use cases.

Chapter 8, Deploying Azure Data Factory Pipelines, describes how to manually and automatically deploy Azure Data Factory pipelines using the Azure portal and Azure DevOps, respectively.

Chapter 9, Batch and Streaming Data Processing with Azure Databricks, covers recipes to perform batch and streaming data processing using Azure Databricks.

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