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Azure Data Engineering Cookbook

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

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Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781803246789
Length 608 pages
Edition 2nd Edition
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Authors (3):
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Ahmad Osama Ahmad Osama
Author Profile Icon Ahmad Osama
Ahmad Osama
Nagaraj Venkatesan Nagaraj Venkatesan
Author Profile Icon Nagaraj Venkatesan
Nagaraj Venkatesan
Luca Zanna Luca Zanna
Author Profile Icon Luca Zanna
Luca Zanna
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Toc

Table of Contents (16) Chapters Close

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 15. Other Books You May Enjoy

Analyzing data using serverless SQL pool

Serverless SQL pool allows us to explore data using T-SQL commands in a Synapse Analytics workspace. The key advantage of serverless SQL pool is that it is available by default once a Synapse Analytics workspace is provisioned with no cluster or additional resources to be created. In serverless SQL pool, you will be charged only for the data processed by the queries as it is designed as a pure pay-per-use model.

Getting ready

Create a Synapse Analytics workspace, as explained in the Provisioning an Azure Synapse Analytics workspace recipe of this chapter.

How to do it…

In this recipe, we will perform the following:

  • Uploading sample data into a Synapse Analytics workspace data lake account and querying it using serverless SQL pool
  • Creating a serverless SQL database and defining a view to read the data stored in the data lake account

The detailed steps to perform these tasks are as follows:

  1. Log...
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