ELEVEN MYTHS ABOUT DATA ANALYTICS FOR IOT DEVICE FLEETS

Published in Electronic Design:

ABSTRACT: IoT device fleets are becoming more pervasive. As devices are becoming connected to the Internet, new possibilities for how to use the data are opening up. For any IoT solution, maturity occurs in three stages: (1) connected, (2) managed, and (3) optimized. Data analytics maturity mirrors these three steps: (1) when devices are connected we can get some descriptive data about them; (2) when devices are managed, we can generate predictive analytics on them to figure out what might happen in the future such as with a motor failure; and (3) we can optimize devices and user interactions by using prescriptive analytics to provide closed loop feedback. This article lays out the foundations of data analytics and data science for IoT device deployments, and recommendations for success.

It's not magic, it's data. 11 data analytics myths busted: https://t.co/8YKWlq2aXz @markbenson @Electronic Design #IoT

— General Assembly (@GA) April 15, 2016