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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

Product type Paperback

Published in Jul 2017

Publisher Packt

ISBN-13 9781787120730

Length 378 pages

Edition 1st Edition

Languages

Scala

Tools

Apache Spark

Concepts

Single Board Computers

Author (1):

Andrew Minteer

View More author details

Table of Contents (14) Chapters

Preface

1. Defining IoT Analytics and Challenges

2. IoT Devices and Networking Protocols FREE CHAPTER

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

Designing data processing for analytics

There are some key cloud services that are likely to be employed in your IoT data processing environment. Both AWS and Microsoft Azure have IoT-specific services that we will review. There are also services that support data processing and transformation that are worth a review to increase your familiarity with them.

Amazon Kinesis

Amazon Kinesis is a set of services for loading and analyzing streaming data. It handles all the underlying compute, storage, and messaging services for you.

The services in the Kinesis family are as follows:

Amazon Kinesis Firehose: This enables loading of massive volumes of streaming data into AWS.
Amazon Kinesis Streams: This service allows you to create custom applications to process and analyze streaming data in real time. There are two ends to each stream; you use the Amazon Kinesis Producer Library (KPL) to build the application that sends data into the stream. The Amazon Kinesis Client Library (KCL) is used in the application...

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Authors (1)

Andrew Minteer

Andrew Minteer

Andrew Minteer is currently the senior director, data science and research at a leading global retail company. Prior to that, he served as the director, IoT Analytics and Machine Learning at a Fortune 500 manufacturing company. He has an MBA from Indiana University with a background in statistics, software development, database design, cloud architecture, and has led analytics teams for over 10 years. He first taught himself to program on an Atari 800 computer at the age of 11 and fondly remembers the frustration of waiting through 20 minutes of beeps and static to load a 100-line program. He now thoroughly enjoys launching a 1 TB GPU-backed cloud instance in a few minutes and getting right to work. Andrew is a private pilot who looks forward to spending some time in the air sometime soon. He enjoys kayaking, camping, traveling the world, and playing around with his six-year-old son and three-year-old daughter.

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