Book Image

Cloud Analytics with Google Cloud Platform

By : Sanket Thodge
Book Image

Cloud Analytics with Google Cloud Platform

By: Sanket Thodge

Overview of this book

With the ongoing data explosion, more and more organizations all over the world are slowly migrating their infrastructure to the cloud. These cloud platforms also provide their distinct analytics services to help you get faster insights from your data. This book will give you an introduction to the concept of analytics on the cloud, and the different cloud services popularly used for processing and analyzing data. If you’re planning to adopt the cloud analytics model for your business, this book will help you understand the design and business considerations to be kept in mind, and choose the best tools and alternatives for analytics, based on your requirements. The chapters in this book will take you through the 70+ services available in Google Cloud Platform and their implementation for practical purposes. From ingestion to processing your data, this book contains best practices on building an end-to-end analytics pipeline on the cloud by leveraging popular concepts such as machine learning and deep learning. By the end of this book, you will have a better understanding of cloud analytics as a concept as well as a practical know-how of its implementation
Table of Contents (16 chapters)
Title Page
Packt Upsell
Foreword
Contributors
Preface
Index

Chapter 9. Introduction to AWS and Azure

In this Appendix, we are going to learn about two prominent cloud vendors—Amazon Web Services (AWS) and Microsoft Azure. Firstly, I will be introducing you to AWS, and then to Azure. After having a brief overview of AWS and Azure, we will have a look at all the services that these major vendors provide.

And once you are familiar with the ecosystem of AWS and Azure, we can compare them to Google Cloud Platform (GCP)—head to head.

We will be discussing the following topics:

  • Overview of AWS services
  • Overview of Azure services
  • Head-to-head comparison between AWS, Azure, and GCP