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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

Unstructured Data Management

Unstructured data is said to constitute a huge portion of data generated today. Some industry studies say at least 85% of data available today is unstructured. So, what is this unstructured data? Data with no predefined external structure in the form of a schema or table (rows and columns), object structure (JSON, XML, and so on), or data model is termed unstructured data, even though such data can have an internal structure. It can be generated by machines, humans, or applications.

Some common examples and sources of unstructured data are images, audio, video, files, and rich media. The fact that it is not constrained by fixed schema and is flexible for analyzing and drawing insights from raw data as-is is one of the major advantages of this type of data management. However, industries and organizations are not able to take full advantage of data of this kind for many reasons:

  • The complexity involved in terms of data storage, management, processing...
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