Scaling Data Science for the Industrial Internet of Things

Описание

One estimate holds that, by 2020, businesses involved with the Internet of Things will spend roughly 26% of their entire IoT cost on technologies and services that store, integrate, visualize, and analyze data from various IoT devices—or nearly twice what IoT companies spend today. Conventional techniques for extracting and evaluating IoT data need to get a lot smarter if companies are to keep pace with the phenomena they’re tracking.

In this report, author Andy Oram discusses the state of IoT analytics by examining ThingWorx and its partners Glassbeam and National Instruments—companies that provide development tools and capabilities for building and running IoT applications. By learning how to use modern techniques to automate and speed up analytics on IoT projects, you can gain an edge in security, customer satisfaction, and operational efficiencies.

• Understand the demands of IoT analytics by exploring examples of farm, factory, vehicle maintenance, and healthcare automation
• Explore the characteristics of predictive analytics, a realm where you don’t know in advance which factors are relevant
• Examine the tools for IoT analytics used by companies at various levels of data analytics
• Get revealing case studies of IoT analytics from ThingWorx, Glassbeam, and National Instruments