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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Build faster and efficient real-world applications on the cloud with a fitting database model that’s perfect for your needs
Key FeaturesFamiliarize yourself with business and technical considerations involved in modeling the right databaseTake your data to applications, analytics, and AI with real-world examplesLearn how to code, build, and deploy end-to-end solutions with expert advicePurchase of the print or Kindle book includes a free PDF eBookBook 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 learnUnderstand different use cases and real-world applications of data in the cloudWork with document and indexed NoSQL databasesGet to grips with modeling considerations for analytics, AI, and MLUse real-world examples to learn about ETL servicesDesign structured, semi-structured, and unstructured data for your applications and analyticsImprove observability, performance, security, scalability, latency SLAs, SLIs, and SLOsWho 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.
Table of ContentsData, Databases, and DesignHandling Data on the CloudDatabase Modeling for Structured DataSetting Up a Fully Managed RDBMSDesigning an Analytical Data WarehouseDesigning for Semi-structured DataUnstructured Data ManagementDevOps and DatabasesData to AI – Modeling Your Databases for Analytics and MLLooking Ahead – Designing for LLM Applications
ASIN : B0CQG9QD7C
Publisher : Packt Publishing; 1st edition (December 29, 2023)
Publication date : December 29, 2023
Language : English
File size : 14079 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 360 pages
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Puneet Srivastava –
âDatabase Design and Modeling with Google Cloudâ: A Practical Guide
Recently, Iâve been quite busy, but I finally managed to dive into the book âDatabase Design and Modeling with Google Cloudâ. It has been an enjoyable read, serving as both a refresher and an exploration of various topics related to Google Cloud. Let me share my thoughts on this insightful book.Introduction and Focus:The book doesnât attempt to be an exhaustive encyclopedia; instead, it focuses on introducing essential concepts to beginners on the GCP platform. Specifically, it delves into database setup and configuration within the Google Cloud ecosystem. The authorâs intention is clear: provide practical guidance rather than overwhelming readers with generic information.Step-by-Step Guidance:The book offers a step-by-step guide for setting up and configuring different variations of database deployment capabilities on Google Cloud Platform (GCP). These include Google Cloud SQL, BigQuery, and Firestore.Additionally, it provides a quick overview of storage concepts and Continuous Integration/Continuous Deployment (CI/CD) capabilities on GCP.AI & LLMs:The book walks through ingesting data and demonstrates how to use Google Colab to create a notebook for running a sample model. This practical approach helps readers implement their first solutions effectively.Furthermore, the book includes a guided walkthrough on leveraging LLM (Looker, Language, and Machine Learning) using Vertex AI and BigQuery. This combination bridges theory and real-world application.Kudos to the author, for keeping the book grounded in practicality. Itâs refreshing to have a resource that focuses on actionable steps rather than abstract theory.While the book is commendable, clearer screenshots could enhance the readerâs experience. Perhaps future editions can address this.In summary, âDatabase Design and Modeling with Google Cloudâ is an excellent companion for anyone beginning their journey on the Google Cloudâs data offerings. Whether youâre a beginner or need a refresher, this book provides valuable insights and practical guidance.
Richard L. Seroter –
Learn the right ways to use modern cloud data services
Disclosure: I work with Abi at Google CloudIf youâre building a modern data strategy or working with Google Cloud, this is a required book for your bookshelf. The author clearly explains now just the âhowâ but the âwhyâ youâd make a given choice. I enjoyed the author’s writing style which was clear and often went the extra-mile to explain a concept.The book looks at topics around choosing the correct database for a given use case, how to set up and configure a variety of Cloud databases, how to think about automated deployments, what a database migration might look like, and how to think about data and LLM apps. These aren’t trivial things to understand in a cloud environment, and I thought the author did a very good job providing each topic with the correct amount of depth.If youâre looking for a tutorial on generic data warehousing or database design, this isnât that book. You wonât find instructions on creating a star schema or choosing between stored procedures or user-defined functions. But this is a book that will give you the right context and the right confidence to successfully use Google Cloud data services in your architecture.
Dieter –
Cloud Computing Meets Database Design: A Review of Database Design & Modeling with Google Cloud
“Database Design & Modeling with Google Cloud” by Abirami Sukumaran is a comprehensive guide for data professionals in cloud database design and modeling. This book begins with foundational concepts of databases and design, then delves into structured, semi-structured, and unstructured data, covering aspects like data modeling, technical considerations, and choosing the right database.The book is well-structured, offering insights into cloud computing benefits, database types like relational and NoSQL, and practical applications in cloud services like Cloud SQL and BigQuery. It uniquely integrates database design with advanced topics like AI and ML, providing a holistic view of data management in the cloud era.The author, with her extensive experience, offers a practical approach, making it an excellent resource for database developers, data engineers, architects, and analysts looking to harness Google Cloud services. The book’s strength lies in its practical examples, real-world use cases, and hands-on design considerations, making it valuable for both novices and seasoned professionals in the field of database design and cloud computing.
Amazon Customer –
Good read overall!
As one of the technical reviewers of this newly published book, I really feel fortunate to be a part of this project. Here’s few things I want to highlight about the book:1. First things first, Congratulations to the author Abirami Sukumaran! I gave her some hard time with my reviews and she has been gracious to accept the feedback to re-write some of the content! Kudos to her!2. Industry leaders like Priyanka Vergadia & Bagirathi Narayanan have been kind enough to give their forewords for this book. Cant get better than this!3. IMHO, the book has a good mix of depth & breadth of the topics covered. As the title suggests, this is into over databases design and not much data engineering though.4. Google Cloud services have been explained in simple terms with relevant examples so the reader can easily follow it and apply at workplace.5. BEST PART, all proceeds from the sale of this book goes to charity. So go and grab your copy in Amazon!Thank you to the Packt team for giving me this opportunity to enrich myself and make good use of my free time!
Aisswarya –
Database Design and Modeling with Google Cloud, I got this wonderful book and began to read it immediately. Now, I really want to share my thoughts on this amazing book.The book gives a complete guide on using cloud computing and databases. It provides a detailed introduction and  series of informative questions and answers. It further gives us steps on how to configure the product as well as practice with GCP products. This also makes it a good resource for beginners and professionals who want to gain a better understanding of Google cloud products and knowledge about the database design and modeling .Throughout the book, the author, Abirami Sukumran guides the reader through a systematic approach to database design and modeling using Google Cloud. The book explains the fundamental concepts of data and illustrates how to transform it into artificial intelligence(AI). The book offers a detailed explanation of each step involved in database design and modeling, making it an excellent resource for beginners as well as experienced professionals. Overall, this book provides a comprehensive understanding of database design and modeling with Google Cloud.In the end, this book is all you need if you want to begin learning cloud computing and database from nothing.
AKSHAY BHOPANI –
A must have for people who work with data digitallyThis book starts with basics and history of database, database types, database languages and goes deep into factors considering the Database Design and Modelling.It gives you hands on experience with working with databases on Google Cloud. Not only that you could actually find most of the database types and its actual service name in Google Cloud.For example-Key-value database: MemorystoreWide-column database: BigtableIt gives real world applications based examples for creating and updating data in SQL and Java Code. Loved the Questionnaire format, it gives answers to most of the questions in your mind.It tells how a transactional database is different from analytical databases and how data warehousing can help businesses to efficiently manage their data and get useful analytics from it.Then it covers BigQuery and why it is the best database warehouse with the ability to connect to public datasets with free 1TB of data querying useful for analytics, business intelligence and data to AI.Then it moves to unstructured database, its use cases and JSON examples. Explaining why FireStore is good choice for document database with its indexing capabilities and support for web and mobile SDKâs. Found the RunQuery API part most useful.Then it covers the Unstructured data which as per some industry studies covers more than 85% of total data available today. Explaining how we can use combination of Cloud Storage and BigQuery to manage and query unstructured data.Then it moves to Updates, Security, Monitoring and CI/CD Operations with Cloud Build, Cloud Code and Cloud Deploy. Loved the real world example of importing MySql Data to Cloud SQL via Data Migration API.Then it moves to Google Cloud Dataflow which is ETL service that is use to migrate and manage data with a pipeline demo in Java and Maven which to be honest gone above my head.Then the exciting part is taking that imported data to AI with a real world example of identifying context using word2vec and cosine similarity techniques in python.Then it covers LLM Basics and its best practices with hands on example of building a LLM application in BigQuery which can read text from BigQuery Database and generate two line of explanation from it.This book is absolute masterpiece and highly recommended for people who work with databases and cloud.