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Architecting Google Cloud Solutions

You're reading from   Architecting Google Cloud Solutions Learn to design robust and future-proof solutions with Google Cloud technologies

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Product type Paperback
Published in Apr 2021
Publisher Packt
ISBN-13 9781800563308
Length 472 pages
Edition 1st Edition
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Author (1):
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Victor Dantas Victor Dantas
Author Profile Icon Victor Dantas
Victor Dantas
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Table of Contents (17) Chapters Close

Preface 1. Section 1: Introduction to Google Cloud
2. Chapter 1: An Introduction to Google Cloud for Architects FREE CHAPTER 3. Chapter 2: Mastering the Basics of Google Cloud 4. Section 2: Designing Great Solutions in Google Cloud
5. Chapter 3: Designing the Network 6. Chapter 4: Architecting Compute Infrastructure 7. Chapter 5: Architecting Storage and Data Infrastructure 8. Chapter 6: Configuring Services for Observability 9. Chapter 7: Designing for Security and Compliance 10. Section 3: Designing for the Modern Enterprise
11. Chapter 8: Approaching Big Data and Data Pipelines 12. Chapter 9: Jumping on the DevOps Bandwagon with Site Reliability Engineering (SRE) 13. Chapter 10: Re-Architecting with Microservices 14. Chapter 11: Applying Machine Learning and Artificial Intelligence 15. Chapter 12: Achieving Operational Excellence 16. Other Books You May Enjoy

Choosing the right storage solution

A fundamental skill for any cloud architect is to know how to choose the right storage solution for the various types of data an organization possesses. In this section, you will start by learning a mental framework that will make it easier for you to make the right choice of data solution. Let's start by understanding and identifying the different types of data that exist.

Types of data

Data can be categorized in a few different "dimensions," so let's look at each one of them separately.

Relational versus non-relational

This first distinction applies to whether or not datasets are organized according to the relational model for databases. A collection of tables of data is considered relational when the relationship between the different tables is important. For example, suppose you have a table containing employees' data, such as their name, department, and salary, and you have another table containing department...

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