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

Exercise

Figure 7.15 shows the ERD of Northwind that you saw in Chapter 2, Entity Analysis. Northwind is a company that purchases delicacies (products) from suppliers all over the world. The products have been categorized into categories. Products are sold to customers by Northwind employees. Shippers make sure that customers receive the products they buy:

Figure 7.15 – Northwind ERD

Because management feels they lack control because they lack information, you are asked to create management reports based on a star schema database. Following an initial analysis, the following demands have been formulated:

  • The sales department needs reports showing sales by customer, by salesperson, by product, by supplier, and by country:

    a. All reports should be based on fiscal years starting on July 1.

    b. An analysis needs to be broken down from years into quarters and months. When an analysis is performed based on the calendar rather than on fiscal years, trimesters...