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

An alternative approach to normalizing data

In the previous section, we normalized one report. In real life, there will be a multitude of reports, screens, and forms to analyze. A lot of them will use the same columns. To create a complete database schema, we need to analyze and normalize all of them. For now, let's assume that there is a second report, Project Progress, that we need to normalize. You can see the report in Figure 3.13:

Figure 3.13 – Project progress

We could go through all the formal steps for this report as we have done for the first report. Instead, we will use an alternative approach. This method sort of involves combining entity analysis and normalizing data. In real life, experienced database designers do not go through all the formal steps. Some even say that we no longer normalize nowadays, but not doing the formal steps explicitly doesn't mean you are not applying the underlying theory.

Step 1

The first step to...