Author Archive

Two reasons machine learning is warming up for industrial companies

Machine learning isn’t new.  Expert systems were a strong research topic in the 1970’s and 1980’s and often embodied machine learning approaches.  Machine learning is a subset of predictive analytics, a subset that is highly automated, embedded, and self-modifying.  Currently, enthusiasm for machine learning is seeing a strong resurgence, with two factors driving that renewed interest: more

Industrial IoT Platform Capabilities

According to ARC there are 8 broad capabilities that a well-rounded platform for the Industrial Internet of Things needs to have.  In no particular order: more

How to decide which analytics you need for Industrial IoT?

That, as I believe Shakespeare almost said once, is the question.  I’ve written before that, at the highest level, ARC thinks about analytics in four categories:  Describe, Discover, Predict and Prescribe.  That’s fine, it gives us a nice cozy way to bucket business intelligence, operational intelligence, and analytics tools and solutions.  But, that’s as far as it goes.  As a model, it doesn’t help technology buyers figure out what is the appropriate type of solution for any particular situation.  To work through that process calls for something different. more

Prescriptive analytics and Industrial IoT: Growing up together

Prescriptive analytics is a bit of a unicorn – a thing of beauty, but rarely seen.  I think that’s about to change, with prescriptive analytics and the Industrial Internet of Things (IIoT) enjoying their teenage years together.  Other styles of analytics (Describe, Discover and Predict) are inherently dependent on subject matter experts (SMEs) for interpretation.  That is, to a large extent current analytics tools and applications present data and information, but with little related business context.  So, a SME is required to infer the context and work their way towards a decision, based partly on data, partly on their expertise, and partly on intuition. more