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Database Design and Modeling with Google Cloud

Database Design and Modeling with Google Cloud

By : Sukumaran
4.9 (7)
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Database Design and Modeling with Google Cloud

Database Design and Modeling with Google Cloud

4.9 (7)
By: Sukumaran

Overview of this book

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.
Table of Contents (18 chapters)
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1
Part 1:Database Model: Business and Technical Design Considerations
4
Part 2:Structured Data
8
Part 3:Semi-Structured, Unstructured Data, and NoSQL Design
11
Part 4:DevOps and Databases
13
Part 5:Data to AI

System, query, and performance insights

Understanding the functioning of your database system, application, performance, cost, and security-related factors are key considerations when it comes to database operations and observability. Google Cloud provides insights on system, query, performance, cost, security, and so on. System insights allow you to track important attributes such as system usage, availability, CPU utilization, disk utilization, database load, and so on, and proactively focus on finding patterns and taking actions. Query insights provide help in the detection and diagnosis of issues in the performance of your instance by examining queries in your application. There are more such insights. These insights provide information using historical and near real-time data, and at the same time, provide actionable prescriptive alerts with regard to your services. If you can enable these for your data and application, where available, you will be able to enhance the performance...

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