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Azure Data Engineering Cookbook

Azure Data Engineering Cookbook

By : Ahmad Osama, Nagaraj Venkatesan
4.2 (12)
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Azure Data Engineering Cookbook

Azure Data Engineering Cookbook

4.2 (12)
By: Ahmad Osama, Nagaraj Venkatesan

Overview of this book

Data engineering is one of the faster growing job areas as Data Engineers are the ones who ensure that the data is extracted, provisioned and the data is of the highest quality for data analysis. This book uses various Azure services to implement and maintain infrastructure to extract data from multiple sources, and then transform and load it for data analysis. It takes you through different techniques for performing big data engineering using Microsoft Azure Data services. It begins by showing you how Azure Blob storage can be used for storing large amounts of unstructured data and how to use it for orchestrating a data workflow. You'll then work with different Cosmos DB APIs and Azure SQL Database. Moving on, you'll discover how to provision an Azure Synapse database and find out how to ingest and analyze data in Azure Synapse. As you advance, you'll cover the design and implementation of batch processing solutions using Azure Data Factory, and understand how to manage, maintain, and secure Azure Data Factory pipelines. You’ll also design and implement batch processing solutions using Azure Databricks and then manage and secure Azure Databricks clusters and jobs. In the concluding chapters, you'll learn how to process streaming data using Azure Stream Analytics and Data Explorer. By the end of this Azure book, you'll have gained the knowledge you need to be able to orchestrate batch and real-time ETL workflows in Microsoft Azure.
Table of Contents (11 chapters)
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Querying the data in a lake database from serverless SQL pool

Lake databases are created from Synapse Spark pools and typically consist of Delta tables. The following recipe will showcase how we could read the data stored in Delta tables from serverless SQL pool.

Getting ready

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

Create a Spark pool, as explained in the Provisioning and configuring Spark pools recipe in this chapter.

Create a lake database and Delta table, as explained in the Processing data using Spark pools and lake database recipe in this chapter.

How to do it…

Perform the following steps to query the data:

  1. Log in to portal.azure.com, click All Resources, search for packtadesynapse, the Synapse Analytics workspace that we created, and click on it. Click Open Synapse Studio. Click on the data icon on the left, click the Linked tab, and expand the Azure Data...
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Azure Data Engineering Cookbook
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