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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

Data to AI – Modeling Your Databases for Analytics and ML

Businesses rely on analytics to gain valuable insights and make informed decisions. Cloud databases have emerged as a powerful platform for storing and analyzing large volumes of data. To leverage the full potential of cloud databases for analytics, effective data modeling is crucial. It involves a deep focus on the needs of data analysts, business intelligence, and data operations teams. It involves designing a database that is optimized for data analysis, such as querying, reporting, and visualization, and by extension for advanced analytics, such as machine learning (ML) and artificial intelligence (AI). In this chapter, we’ll explore some key considerations and best practices for data modeling for analytics, ML and AI in cloud databases.

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

  • Modeling considerations for analytics, AI, and ML
  • Data to AI
  • Google Cloud ETL services
  • Google...
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