Data Modeling for Azure Data Services

Choose the right Azure data service and correct model design for successful implementation of your data model with the help of this hands-on guide

Key Features

• Design a cost-effective, performant, and scalable database in Azure
• Choose and implement the most suitable design for a database
• Discover how your database can scale with growing data volumes, concurrent users, and query complexity

Book Description

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.

What you will learn

• Model relational database using normalization, dimensional, or Data Vault modeling
• Provision and implement Azure SQL DB and Azure Synapse SQL Pools
• Discover how to model a Data Lake and implement it using Azure Storage
• Model a NoSQL database and provision and implement an Azure Cosmos DB
• Use Azure Data Factory to implement ETL/ELT processes
• Create a star schema model using dimensional modeling

Who this book is for

This book is for business intelligence developers and consultants who work on (modern) cloud data warehousing and design and implement databases. Beginner-level knowledge of cloud data management is expected.

Table of Contents

1. Introduction to Databases
2. Entity Analysis
3. Normalizing Data
4. Provisioning and Implementing an Azure SQL DB
5. Design a NoSQL Database
6. Provisioning and Implementing an Azure Cosmos DB Database
7. Dimensional Modeling
8. Provision and implement an Azure Synapse SQL Pool
9. Data Vault Modeling
10. Designing and Implementing a Data Lake Using Azure Storage
11. Implementing ETL Using Azure Data Factory

Peter Ter Braake started working as a developer in 1996 after studying physics in Utrecht, the Netherlands. Databases and business intelligence piqued his interest the most, leading to him specializing in SQL Server and its business intelligence components. He has worked with Power BI from the tool's very beginnings. Peter started working as an independent contractor in 2008. This has enabled him to divide his time between teaching data-related classes, consulting with customers, and writing articles and books.