Human-centric, data-to-decision analytics for the Industrial Internet of Things (IIoT)

As companies engage in the implementation of analytics and data science applications, many challenges lie ahead. According to the Harvard Business Review, many data science applications fail due to poor goal definition, a lack of understanding of the key data, or a lack of focus on business value. Allows engineers to use the platform and be part of the analytics process. This article takes a look at each of these elements in further detail and explores why they are important to driving value for your organization. Having a platform built on your subject matter experts' knowledge is the best starting point.