Book Image

Data Modeling for Azure Data Services

By : Peter ter Braake
Book Image

Data Modeling for Azure Data Services

By: Peter ter Braake

Overview of this book

Data is at the heart of all applications and forms the foundation of modern data-driven businesses. With the multitude of data-related use cases and the availability of different data services, choosing the right service and implementing the right design becomes paramount to successful implementation. Data Modeling for Azure Data Services starts with an introduction to databases, entity analysis, and normalizing data. The book then shows you how to design a NoSQL database for optimal performance and scalability and covers how to provision and implement Azure SQL DB, Azure Cosmos DB, and Azure Synapse SQL Pool. As you progress through the chapters, you'll learn about data analytics, Azure Data Lake, and Azure SQL Data Warehouse and explore dimensional modeling, data vault modeling, along with designing and implementing a Data Lake using Azure Storage. You'll also learn how to implement ETL with Azure Data Factory. By the end of this book, you'll have a solid understanding of which Azure data services are the best fit for your model and how to implement the best design for your solution.
Table of Contents (16 chapters)
1
Section 1 – Operational/OLTP Databases
8
Section 2 – Analytics with a Data Lake and Data Warehouse
13
Section 3 – ETL with Azure Data Factory

Executing SQL code from Data Factory

Azure Data Factory, and through Data Factory, Synapse integration, lets you choose the most suitable way to load data into a Synapse SQL pool. You just used the code-less option by implementing a Data Factory data flow. You already imported data into your Synapse SQL pool using T-SQL code in Chapter 8, Provisioning and Implementing an Azure Synapse SQL Pool. Let's have a quick look at how to automate the option where you use T-SQL code using Synapse pipelines.

In the following section, we will assume that you have implemented the dimDate, dimCustomer, dimProduct, and factOrder tables, as discussed and created in Chapter 8, Provisioning and Implementing an Azure Synapse SQL Pool. We will create a stored procedure in the SQL database and execute it using a pipeline activity. The stored procedure will do a full load of the factOrder table based on the exports of the dbo.Order and dbo.OrderDetail tables you created in the section regarding the...