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Data Modeling for Azure Data Services

You're reading from   Data Modeling for Azure Data Services Implement professional data design and structures in Azure

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781801077347
Length 428 pages
Edition 1st Edition
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Author (1):
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Peter ter Braake Peter ter Braake
Author Profile Icon Peter ter Braake
Peter ter Braake
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Table of Contents (16) Chapters Close

Preface 1. Section 1 – Operational/OLTP Databases
2. Chapter 1: Introduction to Databases FREE CHAPTER 3. Chapter 2: Entity Analysis 4. Chapter 3: Normalizing Data 5. Chapter 4: Provisioning and Implementing an Azure SQL DB 6. Chapter 5: Designing a NoSQL Database 7. Chapter 6: Provisioning and Implementing an Azure Cosmos DB Database 8. Section 2 – Analytics with a Data Lake and Data Warehouse
9. Chapter 7: Dimensional Modeling 10. Chapter 8: Provisioning and Implementing an Azure Synapse SQL Pool 11. Chapter 9: Data Vault Modeling 12. Chapter 10: Designing and Implementing a Data Lake Using Azure Storage 13. Section 3 – ETL with Azure Data Factory
14. Chapter 11: Implementing ETL Using Azure Data Factory 15. Other Books You May Enjoy

Preface

Databases play an important role in almost all the applications that we use. The database has a direct impact on the performance and scalability of the application it supports. That makes choosing the right type of database to use and designing that database correctly a vital part of all development since scalability and performance depend on a well-chosen design. With databases hosted in Azure, the design may also have a direct impact on the costs of the database. The first part of this book teaches you when to use a relational database (Azure SQL Database) and when a NoSQL database (Cosmos DB) is the better option. You will also learn how to design that database and, finally, how to implement the chosen design.

All the data gathered by applications can be used for Business Intelligence (BI). A crucial part of BI is creating a central repository for your data to build your BI solution on. This can be a data lake with data marts, or it may be a data warehouse. In the second part of the book, you will learn to design data warehouses according to the theory of dimensional modeling or by designing a data vault. You will also learn how to design a data lake. You will then learn how to apply what you have learned by creating a data lake in Azure Storage and creating data marts using Azure Synapse Analytics.

The book ends with a chapter on Azure Data Factory. Data Factory is used to get data from the source databases you created in part one and store that data in the data platforms you implemented in part two.

After reading this book, you have a solid understanding of data modeling and of how to implement a database schema in Azure. This will help you to build scalable and cost-effective data solutions in Azure.

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