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)

What this book covers

Chapter 1, Working with Azure Blob Storage, covers how to work with Azure Blob storage and understand how it is used when orchestrating a data workflow.

Chapter 2, Working with Relational Databases in Azure, explains how to provision and work with Azure SQL Database.

Chapter 3, Analyzing Data with Azure Synapse Analytics, describes how to provision an Azure Synapse database and ingest and analyze data in Azure Synapse.

Chapter 4, Control Flow Activities in Azure Data Factory, explains how to implement different control activities available in Azure Data Factory.

Chapter 5, Control Flow Transformation and the Copy Data Activity in Azure Data Factory, explains how to work with the Azure Data Factory integration runtime. You'll also learn to use the SSIS package with Azure Data Factory.

Chapter 6, Data Flow in Azure Data Factory, explains how to use Azure Data Factory mapping and wrangling data flow to extract, transform, and load data.

Chapter 7, Azure Data Factory Integration Runtime, details the different integration runtimes available and their use cases.

Chapter 8, Deploying Azure Data Factory Pipelines, describes how to manually and automatically deploy Azure Data Factory pipelines using the Azure portal and Azure DevOps, respectively.

Chapter 9, Batch and Streaming Data Processing with Azure Databricks, covers recipes to perform batch and streaming data processing using Azure Databricks.