Key FeaturesMake better business decisions and acquire greater control of your IoT infrastructureLearn techniques to solve unique problems associated with IoT and examine and analyze data from your IoT devicesUncover the business potential generated by data from IoT devices and bring down business costsBook DescriptionWe 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. Youll 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. Well also review the economics of IoT analytics and youll discover ways to optimize business value.By the end of the book, youll 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 learnOvercome the challenges IoT data brings to analyticsUnderstand the variety of transmission protocols for IoT along with their strengths and weaknessesLearn how data flows from the IoT device to the final data setDevelop techniques to wring value from IoT dataApply geospatial analytics to IoT dataUse machine learning as a predictive method on IoT dataImplement best strategies to get the most from IoT analyticsMaster the economics of IoT analytics in order to optimize business valueAbout the AuthorAndrew 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.Table of ContentsDefining IoT Analytics and ChallengesIoT Devices and Networking ProtocolsIoT Analytics for the CloudCreating an AWS Cloud Analytics EnvironmentCollecting All That Data - Strategies and TechniquesGetting to Know Your Data - Exploring IoT DataDecorating Your Data - Adding External Datasets to InnovateCommunicating with Others - Visualization and DashboardingApplying Geospatial Analytics to IoT DataData Science for IoT AnalyticsStrategies to Organize Data for AnalyticsThe Economics of IoT AnalyticsBringing It All Together