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

Designing business vaults

The first version of the Data Vault theory introduced the notion of Hubs, Links, and Satellites. This provided the flexibility over time that we needed for data warehousing. Data Vault 2.0 has a couple of adaptions to the first version. An important change was the introduction of hash keys. But Data Vault 2.0 also introduced the concept of a business vault. This addresses the fact that the structure of a Data Vault as discussed until now will rapidly become complex and difficult to query. The latter leads inevitably to bad query performance.

The introduction of the business vault led to two other new terms: Raw Data Vault and Operational Data Vault. Both terms mean the same and refer to a "pure" Data Vault structure with Hubs, Links, and Satellites as discussed so far in this chapter. The Raw Data Vault stores raw data coming directly from the source database. The columns are stored in different table structures, but the data itself is not changed...