Book Image

Azure Data Engineering Cookbook

By : Ahmad Osama
Book Image

Azure Data Engineering Cookbook

By: Ahmad Osama

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)

Chapter 2: Working with Relational Databases in Azure

Microsoft Azure provides Azure SQL Database, PostgreSQL, and MySQL as Database-as-a-Service offerings. We can create an instance of these databases without worrying about the installation, administration, infrastructure, and upgrades.

Needless to say that we can install any of the available Relational Database Management System (RDBMS) databases, such as Oracle or DB2, on an Azure virtual machine (VM).

In a data pipeline, we can use any of the RDBMS databases as either a source or a destination. In this chapter, we'll learn how to provision, connect to, manage, maintain, and secure these databases.

We'll cover the following recipes in this chapter:

  • Provisioning and connecting to an Azure SQL database using PowerShell
  • Provisioning and connecting to an Azure PostgreSQL database using the Azure CLI
  • Provisioning and connecting to an Azure MySQL database using the Azure CLI
  • Implementing active geo-replication for an Azure SQL database using PowerShell
  • Implementing an auto-failover group for an Azure SQL database using PowerShell
  • Implementing vertical scaling for an Azure SQL database using PowerShell
  • Implementing an Azure SQL database elastic pool using PowerShell
  • Monitoring an Azure SQL database using the Azure portal