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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

Considerations for your RDBMS

There are some considerations and best practices for RDBMS modeling. Here are some of these key considerations:

  • Purpose, functionality, type, and structure: The first step in data modeling is to understand the business requirements. What data do you need to store? How will the data be used? What is the type, structure, and purpose of the data you are dealing with? Once you understand the business requirements, you can start to design the data model.
  • Entities and attributes for the use case: The next step is to identify the entities and attributes in the data model. Entities are the basic building blocks of a data model. They represent real-world objects or concepts. Attributes are the properties of entities. They describe the characteristics of entities.
  • Relationship and dependency of entities and attributes: Once you have identified the entities and attributes, you need to define the relationships between entities. Relationships are the...

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