Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Analytics for the Internet of Things (IoT)

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

Arrow left icon
Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787120730
Length 378 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Andrew Minteer Andrew Minteer
Author Profile Icon Andrew Minteer
Andrew Minteer
Arrow right icon
View More author details
Toc

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

Adding internal datasets


IoT data by itself is only part of the story. There is a multitude of useful data already available to you that could be a store of hidden value. Internal datasets can be overlooked as a way to quickly enhance IoT data. They are an excellent place to start. IoT data should not be viewed in isolation; think of it as a continuation of data already stored about your company's products, customers, and processes.

Data should be combined into a 360-degree view of your business to maximize the opportunity of finding new value in it. The fastest and easiest place to start is usually (but not always) the internal datasets that you already have available.

The reason it may not always be the fastest and easiest comes from internal data security and legacy system hurdles; which can sometimes make it difficult to extract internal data to combine with IoT data. This may be a stumbling block for internal datasets, which, perhaps counter-intuitively, is not the case with external...

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 $19.99/month. Cancel anytime
Banner background image