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)

Implementing a Data Lake Analytics U-SQL activity

Azure Data Lake Analytics is an on-demand analytics service that allows you to process data using R, Python, and U-SQL without provisioning any infrastructure. All we need to do is to upload the data onto Data Lake, provision the Data Lake Analytics account, and run U-SQL to process the data.

In this recipe, we'll implement a Data Lake Analytics U-SQL activity to calculate total sales by country from the orders data stored in the Data Lake store.

Getting ready

To get started, do the following:

  1. Log in to using your Azure credentials.
  2. Open a new PowerShell prompt. Execute the Connect-AzAccount command to log in to your Azure account from PowerShell.
  3. You will need an existing Data Factory account. If you don't have one, create one by executing the ~/azure-data-engineering-cookbook\Chapter04\3_CreatingAzureDataFactory.ps1 PowerShell script.

How to do it…