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)

Executing an SSIS package with an on-premises data store

We may have SSIS packages accessing an on-premises data source or the destination; for example, we may have files in an on-premises file store to be uploaded to Azure SQL Database, or we may have an on-premises database as the source. In such cases, we require the Azure SSIS IR to connect to the on-premises data store. There are two ways to do that:

  • Configuring Azure SSIS to connect to on-premises using a Point-to-Site VPN, Site-to-Site VPN, or ExpressRoute. There are three steps to this:

    1) Set up a Point-to-Site VPN, Site-to-Site VPN, or ExpressRoute between on-premises and Azure.

    2) Create a virtual network and join the Azure SSIS IR with the virtual network.

    3) Create a virtual network gateway.

  • Configure Azure SSIS to use a self-hosted IR as a proxy to connect to on-premises.

In this recipe, we'll explore the second option. To get more information on option 1, you can check out