Break through the hype and learn how to extract actionable intelligence from the flood of IoT data
Key Features
- Make better business decisions and acquire greater control of your IoT infrastructure
- Learn techniques to solve unique problems associated with IoT and examine and analyze data from your IoT devices
- Uncover the business potential generated by data from IoT devices and bring down business costs
Book Description
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
- Defining IoT Analytics and Challenges
- IoT Devices and Networking Protocols
- IoT Analytics for the Cloud
- Creating an AWS Cloud Analytics Environment
- Collecting All That Data - Strategies and Techniques
- Getting to Know Your Data - Exploring IoT Data
- Decorating Your Data - Adding External Datasets to Innovate
- Communicating with Others - Visualization and Dashboarding
- Applying Geospatial Analytics to IoT Data
- Data Science for IoT Analytics
- Strategies to Organize Data for Analytics
- The Economics of IoT Analytics
- Bringing It All Together
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.
