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)

Transforming data using Python

Data transformation at scale is one of the most important uses of Azure Databricks. In this recipe, we'll read product orders from an Azure storage account, read customer information from an Azure SQL Database, join the orders and customer information, apply transformations to filter and aggregate the total order by country and customers, and then insert the output into an Azure SQL Database.

Getting ready

To get started, follow these steps:

  1. Log into using your Azure credentials.
  2. You will need an existing Azure Databricks workspace and at least one Databricks cluster. You can create these by following the Configuring an Azure Databricks environment recipe.

How to do it…

Let's get started by creating an Azure storage account and an Azure SQL database:

  1. Execute the following command to create an Azure Storage account and upload the orders files to the orders/datain container: