Book Image

ETL with Azure Cookbook

By : Christian Cote, Matija Lah, Madina Saitakhmetova
Book Image

ETL with Azure Cookbook

By: Christian Cote, Matija Lah, Madina Saitakhmetova

Overview of this book

ETL is one of the most common and tedious procedures for moving and processing data from one database to another. With the help of this book, you will be able to speed up the process by designing effective ETL solutions using the Azure services available for handling and transforming any data to suit your requirements. With this cookbook, you’ll become well versed in all the features of SQL Server Integration Services (SSIS) to perform data migration and ETL tasks that integrate with Azure. You’ll learn how to transform data in Azure and understand how legacy systems perform ETL on-premises using SSIS. Later chapters will get you up to speed with connecting and retrieving data from SQL Server 2019 Big Data Clusters, and even show you how to extend and customize the SSIS toolbox using custom-developed tasks and transforms. This ETL book also contains practical recipes for moving and transforming data with Azure services, such as Data Factory and Azure Databricks, and lets you explore various options for migrating SSIS packages to Azure. Toward the end, you’ll find out how to profile data in the cloud and automate service creation with Business Intelligence Markup Language (BIML). By the end of this book, you’ll have developed the skills you need to create and automate ETL solutions on-premises as well as in Azure.
Table of Contents (12 chapters)

Data factory creation

This is our first recipe in this chapter. We will create and explore the various Data Factory components. The following recipes will use the same data factory to move and transform data.

As shown in the following diagram, a data factory contains the following components. Azure Storage and SQL Database are not part of the factory; they are just an example of a simple copy activity that Data Factory can do:

Figure 6.1 – An overview of Azure Data Factory

The two main components are triggers and pipelines.

A trigger is essentially a mechanism that starts a pipeline execution. There are three types of triggers:

  • Scheduler: Can be based on a wall clock schedule or based on tumbling windows. A tumbling window essentially triggers the pipeline execution every n time: for example, every 5 minutes, hours, and so on.
  • Event: Detects the presence of a file in an Azure Storage account. Once the file is detected, the pipeline...