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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.

What You Will Learn

  • Overcome the challenges IoT data brings to analytics
  • Understand the variety of transmission protocols for IoT along with their strengths and weaknesses
  • Learn how data flows from the IoT device to the final data set
  • Develop techniques to wring value from IoT data
  • Apply geospatial analytics to IoT data
  • Use machine learning as a predictive method on IoT data
  • Implement best strategies to get the most from IoT analytics
  • Master the economics of IoT analytics in order to optimize business value
Table of Contents

1: DEFINING IOT ANALYTICS AND CHALLENGES

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

 

Authors

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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