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)

Triggering and monitoring our pipeline

We have created our first pipeline and ran it manually in a debug environment. In real-life scenarios, we would schedule a trigger for our pipeline to run. Once the pipeline is scheduled, we want to monitor its runs such as status, row counts, and runtimes. We also want to be alerted when a run fails.

This recipe will show you how it can easily be done with Azure Data Factory. It will teach you how to perform specific actions:

  • Load metadata and accumulate it into a storage account
  • Schedule a trigger to run our pipeline
  • Create an alert for any pipeline failure

Getting ready

This recipe assumes that you have access to an Azure subscription. It can be a free trial one, as described in the Creating an Azure subscription recipe, in Chapter 1, Getting Started with Azure and SSIS 2019. It also assumes that you have created a pipeline from the previous recipe, Moving and transforming data.

How to do it…

Let&apos...