Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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

Arrow left icon
Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781804611456
Length 234 pages
Edition 1st Edition
Concepts
Arrow right icon
Author (1):
Arrow left icon
Abirami Sukumaran Abirami Sukumaran
Author Profile Icon Abirami Sukumaran
Abirami Sukumaran
Arrow right icon
View More author details
Toc

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

Google Cloud ETL services

Google Cloud offers a comprehensive set of services to support ETL workflows, enabling organizations to efficiently process and transform data at scale. These services provide integration, scalability, and managed infrastructure for performing ETL tasks in the cloud. Here are some Google Cloud ETL services:

  • Google Cloud Dataflow: Google Cloud Dataflow is a fully managed service for executing parallel data processing pipelines. It enables developers to build and execute batch or streaming ETL jobs using a unified programming model. Dataflow provides automatic scaling, fault tolerance, and data parallelism, allowing efficient processing of large datasets. It integrates with other Google Cloud services, such as BigQuery, Cloud Storage, and Pub/Sub, making it an ideal choice for ETL workflows.
  • Google Cloud Dataproc: Google Cloud Dataproc is a managed Apache Hadoop and Apache Spark service. It offers a scalable and cost-effective environment for processing...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime