Book Image

Analytics for the Internet of Things (IoT)

By : Andrew Minteer
5 (1)
Book Image

Analytics for the Internet of Things (IoT)

5 (1)
By: Andrew Minteer

Overview of this book

We start with the perplexing task of extracting value from huge amounts of barely intelligible data. The data takes a convoluted route just to be on the servers for analysis, but insights can emerge through visualization and statistical modeling techniques. You will learn to extract value from IoT big data using multiple analytic techniques. Next we review how IoT devices generate data and how the information travels over networks. You’ll get to know strategies to collect and store the data to optimize the potential for analytics, and strategies to handle data quality concerns. Cloud resources are a great match for IoT analytics, so Amazon Web Services, Microsoft Azure, and PTC ThingWorx are reviewed in detail next. Geospatial analytics is then introduced as a way to leverage location information. Combining IoT data with environmental data is also discussed as a way to enhance predictive capability. We’ll also review the economics of IoT analytics and you’ll discover ways to optimize business value. By the end of the book, you’ll know how to handle scale for both data storage and analytics, how Apache Spark can be leveraged to handle scalability, and how R and Python can be used for analytic modeling.
Table of Contents (20 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Summary


In this chapter, we discussed common mistakes when creating visuals for IoT data. Some tips were given to avoid making them. We introduced a method to develop dashboards and visualizations to communicate analytics to an audience. The method has the goal of aligning the visuals to the thought process of the person interacting with them.

We reviewed the use of position on a dashboard to convey importance. The most important piece of information should be in in the upper-left part for cultures that read left to right. Color can also be used effectively to highlight key information to the audience.

Tableau was used to demonstrate how to quickly create a dashboard to communicate your analytics in an interactive way. We walked through an example with the IoT weather data continued from a previous chapter. Some principles of alerting were reviewed along with an example using Tableau.

For further exploration, not discussed here but worthwhile for you to learn, there are also some great visualization...