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Analytics for the Internet of Things (IoT)

You're reading from   Analytics for the Internet of Things (IoT) Intelligent analytics for your intelligent devices

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787120730
Length 378 pages
Edition 1st Edition
Languages
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Author (1):
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Andrew Minteer Andrew Minteer
Author Profile Icon Andrew Minteer
Andrew Minteer
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Table of Contents (14) Chapters Close

Preface 1. Defining IoT Analytics and Challenges FREE CHAPTER 2. IoT Devices and Networking Protocols 3. IoT Analytics for the Cloud 4. Creating an AWS Cloud Analytics Environment 5. Collecting All That Data - Strategies and Techniques 6. Getting to Know Your Data - Exploring IoT Data 7. Decorating Your Data - Adding External Datasets to Innovate 8. Communicating with Others - Visualization and Dashboarding 9. Applying Geospatial Analytics to IoT Data 10. Data Science for IoT Analytics 11. Strategies to Organize Data for Analytics 12. The Economics of IoT Analytics 13. Bringing It All Together

The data retention strategy

Even big data eventually gets too big and costly to maintain. Remembering the goal of minimizing costs while still maximizing value, make sure to develop a retention strategy for IoT data. Data could be simply deleted after it is retained for a certain amount of time. However, by doing this, you could miss out on building a future profitable analytics service that was not thought of before the data was thrown away.

There are other options that allow you to retain value of the data while minimizing the costs. We will discuss some of these next.

Goals

The goals of a retention strategy for IoT analytics are twofold:

  • Maintain Value: Advanced modeling techniques, such as deep learning, need lots of...
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