Database Design and Modeling with Google Cloud: Learn database design and development to take your data to applications, analytics, and AI

Build faster and efficient real-world applications on the cloud with a fitting database model that's perfect for your needs

Key Features:

• Familiarize yourself with business and technical considerations involved in modeling the right database
• Take your data to applications, analytics, and AI with real-world examples
• Learn how to code, build, and deploy end-to-end solutions with expert advice
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description:

In the age of lightning-speed delivery, customers want everything developed, built, and delivered at high speed and at scale. Knowledge, design, and choice of database is critical in that journey, but there is no one-size-fits-all solution. This book serves as a comprehensive and practical guide for data professionals who want to design and model their databases efficiently.

The book begins by taking you through business, technical, and design considerations for databases. Next, it takes you on an immersive structured database deep dive for both transactional and analytical real-world use cases using Cloud SQL, Spanner, and BigQuery. As you progress, you'll explore semi-structured and unstructured database considerations with practical applications using Firestore, cloud storage, and more. You'll also find insights into operational considerations for databases and the database design journey for taking your data to AI with Vertex AI APIs and generative AI examples.

By the end of this book, you will be well-versed in designing and modeling data and databases for your applications using Google Cloud.

What You Will Learn:

• Understand different use cases and real-world applications of data in the cloud
• Work with document and indexed NoSQL databases
• Get to grips with modeling considerations for analytics, AI, and ML
• Use real-world examples to learn about ETL services
• Design structured, semi-structured, and unstructured data for your applications and analytics
• Improve observability, performance, security, scalability, latency SLAs, SLIs, and SLOs

Who this book is for:

This book is for database developers, data engineers, and architects looking to design, model, and build database applications on the cloud with an extended focus on operational consideration and taking their data to AI. Data scientists, as well ML and AI engineers who want to use Google Cloud services in the data to AI journey will also find plenty of useful information in this book. It will also be useful to data analysts and BI developers who want to use SQL impactfully to generate ML and generative AI insights from their data.

以適合您需求的適當資料庫模型，在雲端上建立更快速和高效能的實際應用程式。

主要特點：
- 熟悉在建模正確資料庫時所涉及的商業和技術考量。
- 透過實際案例將您的資料應用於應用程式、分析和人工智慧。
- 學習如何編寫、建立和部署端到端解決方案，並獲得專家建議。
- 購買印刷版或Kindle電子書，即可免費獲得PDF電子書。

書籍描述：
在快速交付的時代，客戶希望一切都能以高速和規模化的方式開發、建立和交付。在這個過程中，資料庫的知識、設計和選擇至關重要，但並不存在一種適用於所有情況的解決方案。本書是資料專業人士的全面實用指南，旨在幫助他們高效地設計和建模資料庫。

本書首先介紹了資料庫的商業、技術和設計考量。接下來，它將帶您深入了解結構化資料庫和分析實際應用案例，使用Cloud SQL、Spanner和BigQuery。隨著進展，您將探索使用Firestore、雲端儲存等實際應用案例的半結構化和非結構化資料庫考量。您還將獲得有關資料庫操作考量以及使用Vertex AI API和生成式AI示例將資料應用於人工智慧的洞察。

通過閱讀本書，您將精通使用Google Cloud設計和建模應用程式的資料和資料庫。

學到什麼：
- 了解雲端中不同使用案例和實際應用程式中的資料。
- 使用文件和索引的NoSQL資料庫。
- 瞭解分析、人工智慧和機器學習的建模考量。
- 通過實際案例學習ETL服務。
- 為應用程式和分析設計結構化、半結構化和非結構化資料。
- 提升資料庫的可觀察性、性能、安全性、可擴展性、延遲SLA、SLI和SLO。

適合閱讀對象：
本書適合資料庫開發人員、資料工程師和架構師，他們希望在雲端上設計、建模和建立資料庫應用程式，並著重於操作考量和將資料應用於人工智慧。同時，資料科學家以及機器學習和人工智慧工程師，如果希望在資料到人工智慧的旅程中使用Google Cloud服務，也會在本書中找到許多有用的資訊。對於希望有效地使用SQL從資料中生成機器學習和生成式人工智慧洞察的資料分析師和BI開發人員也很有用。