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)

Chapter 2: Introducing ETL

When I first started in the data warehousing business, something like 20 years ago, I was asked in an interview to define ETL. Being at my first job interview, I had no clue what the interviewer meant by ETL. Luckily, the interviewer kind of liked me and hired me anyway. He told me that I would know all about ETL quite soon. Being in data warehouse businesses for many years, and more recently a data engineer, ETL is what has kept me busy most of the time since then.

ETL stands for Extract, Transform, and Load. ETL is a data moving technique that has been used in various forms since the first enterprise data warehouses' inceptions.

Microsoft formalized the ETL concept near the end of the 1990s with a tool called DTS: Data Transformation Service. This ETL tool, aimed at helping database administrators load data into and from SQL Server, used SQL and ActiveX to move and transform data on-premises.

Microsoft brought its ETL tool to the cloud with...