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 wrangling data flow

A wrangling data flow performs code-free data preparation at scale by integrating Power Query to prepare/transform data. The Power Query code is converted to Spark and gets executed on a Spark cluster.

In this recipe, we'll implement a wrangling data flow to read the orders.txt file, clean the data, calculate the total sales by country and customer name, and insert the data into an Azure SQL Database table.

Getting ready

To get started, do the following:

  1. Log in to https://portal.azure.com using your Azure credentials.
  2. Open a new PowerShell prompt. Execute the following command to log in to your Azure account from PowerShell:
    Connect-AzAccount
  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.
  4. Create an Azure storage account and upload the files to the ~/Chapter06/Data folder...