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Azure Data Engineering Cookbook

Azure Data Engineering Cookbook - Second Edition

By : Nagaraj Venkatesan, Ahmad Osama
4.6 (13)
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Azure Data Engineering Cookbook

Azure Data Engineering Cookbook

4.6 (13)
By: Nagaraj Venkatesan, Ahmad Osama

Overview of this book

The famous quote 'Data is the new oil' seems more true every day as the key to most organizations' long-term success lies in extracting insights from raw data. One of the major challenges organizations face in leveraging value out of data is building performant data engineering pipelines for data visualization, ingestion, storage, and processing. This second edition of the immensely successful book by Ahmad Osama brings to you several recent enhancements in Azure data engineering and shares approximately 80 useful recipes covering common scenarios in building data engineering pipelines in Microsoft Azure. You’ll explore recipes from Azure Synapse Analytics workspaces Gen 2 and get to grips with Synapse Spark pools, SQL Serverless pools, Synapse integration pipelines, and Synapse data flows. You’ll also understand Synapse SQL Pool optimization techniques in this second edition. Besides Synapse enhancements, you’ll discover helpful tips on managing Azure SQL Database and learn about security, high availability, and performance monitoring. Finally, the book takes you through overall data engineering pipeline management, focusing on monitoring using Log Analytics and tracking data lineage using Azure Purview. By the end of this book, you’ll be able to build superior data engineering pipelines along with having an invaluable go-to guide.
Table of Contents (16 chapters)
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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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Azure Data Engineering Cookbook
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