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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
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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

Designing for Semi-Structured Data

So far, we have discussed relational databases and analytics design for structured data. Now, we will look at semi-structured data and design considerations for it by looking at a hands-on example. In this chapter, you will learn about the fundamentals of semi-structured data with examples and real-world use cases, the characteristics of semi-structured data, design considerations, and the components of a document database. We will also explore setting up and configuring a serverless document database (Firestore), creating indexes, and querying your data with APIs.

In this chapter, we’ll cover the following topics:

  • Semi-structured data
  • NoSQL for semi-structured data
  • Firestore and its features
  • Firestore setup
  • Security
  • Client libraries and APIs
  • Indexing
  • Data model considerations
  • Easy querying with RunQuery API
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