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Database Design and Modeling with Google Cloud

You're reading from   Database Design and Modeling with Google Cloud Learn database design and development to take your data to applications, analytics, and AI

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781804611456
Length 234 pages
Edition 1st Edition
Concepts
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Author (1):
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Abirami Sukumaran Abirami Sukumaran
Author Profile Icon Abirami Sukumaran
Abirami Sukumaran
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Table of Contents (18) Chapters Close

Preface 1. Part 1:Database Model: Business and Technical Design Considerations
2. Chapter 1: Data, Databases, and Design FREE CHAPTER 3. Chapter 2: Handling Data on the Cloud 4. Part 2:Structured Data
5. Chapter 3: Database Modeling for Structured Data 6. Chapter 4: Setting Up a Fully Managed RDBMS 7. Chapter 5: Designing an Analytical Data Warehouse 8. Part 3:Semi-Structured, Unstructured Data, and NoSQL Design
9. Chapter 6: Designing for Semi-Structured Data 10. Chapter 7: Unstructured Data Management 11. Part 4:DevOps and Databases
12. Chapter 8: DevOps and Databases 13. Part 5:Data to AI
14. Chapter 9: Data to AI – Modeling Your Databases for Analytics and ML 15. Chapter 10: Looking Ahead – Designing for LLM Applications 16. Index 17. Other Books You May Enjoy

Data model considerations

When it comes to the data model design choice, we always struggle to choose between a hierarchical (collection group) format and a format closer to a denormalized form (top-level collection) of storing data. Before we get into that, let’s talk about the hierarchical and denormalized formats!

Hierarchical format

The hierarchical format represents information in a structured, nested format. This format is ideal for scenarios where data has clear parent–child relationships or when you want to maintain a well-defined structure. The following is an example of hierarchical data using JSON to represent an organizational hierarchy:

{
  "organization": {
    "name": "XYZ Corporation",
    "departments": [
      {
        "name": "HR",
     ...
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