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Cloud Analytics with Google Cloud Platform

You're reading from   Cloud Analytics with Google Cloud Platform An end-to-end guide to processing and analyzing big data using Google Cloud Platform

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788839686
Length 282 pages
Edition 1st Edition
Concepts
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Author (1):
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Sanket Thodge Sanket Thodge
Author Profile Icon Sanket Thodge
Sanket Thodge
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Table of Contents (11) Chapters Close

Preface 1. Introducing Cloud Analytics 2. Design and Business Considerations FREE CHAPTER 3. GCP 10,000 Feet Above – A High-Level Understanding of GCP 4. Ingestion and Storing – Bring the Data and Capture It 5. Processing and Visualizing – Close Encounter 6. Machine Learning, Deep Learning, and AI on GCP 7. Guidance on Google Cloud Platform Certification 8. Business Use Cases 9. Introduction to AWS and Azure 10. Other Books You May Enjoy

What is cloud analytics?

Now that we know what cloud computing is, let's get started with cloud analytics.

When we talk about cloud analytics we need to understand that what falls under cloud analytics - is that only analytics or data cleaning as well? Is service of showing graphs and report part of cloud analytics? Or not? And do we need to have just one feature among all to be called as a cloud analytics service enabled cloud or we need all of them? Let's have a look on it.

Under cloud analytics we have tools of the data analytics, data processing, and data manipulating. We often go for a subscription based or pay-as-you-go model.

Then we have a definition from Gartner. They says we have six key elements of analytics to define. And these six elements will decide if a cloud vendor is providing cloud analytics or not. The six elements are given below:

  • Data models
  • Processing applications
  • Analytic models
  • Computing power
  • Sharing or storage of results
  • Data sources

If the cloud vendor is having service for serving all the above purpose, then we can say given cloud vendor has cloud analytics services - and now most of the cloud vendor has it.

Examples of cloud analytics products and services include hosted data warehouses, Software-as-a-Service Business Intelligence (SaaS BI), cloud-based social media analytics, or cloud based NoSQL databases.

So far we have discussed the major aspects of what cloud computing and cloud analytics is and the major differences between IaaS and PaaS. Now we are going to discuss the different cloud vendors that we have in the market.

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