Intelligent Actions

Intelligent ActionsIntelligent actions is where the big money will be made with advanced analytics. Analytics in the IoT era is fundamentally different than pre-IoT analytics.  It is critical to understand that the nature and volume of data flowing in IoT changes the nature of the analytics challenge.  In earlier times, even business challenges that were described as “real-time” often had some slack in them relative to many IoT scenarios.  IoT is fundamentally much more demanding.  The vast amount of data flowing means that ACTION must be taken quickly, or the analysis that the action must be based on will simply become out of date.  In IoT, the context changes rapidly, and a new context and situation must be calibrated and calculated on a continuous basis with real-time data flowing into the system.

And then an intelligent action must be taken at that moment, or the value disappears.  This requirement means that Analytics in IoT requires that intelligent – and sometimes automated actions – must be unified with the core analytics engine itself.  It is no longer acceptable to have an execution or process system as an add-on or “after-the-analysis” next system.  That is simply too slow.  Actions must be unified tightly with the unified analytics

Vitria’s IoT Analytics Platform unifies not only all the forms of analytics, but also integrates Intelligent Actions with the Analytics to comprehensively solve the need to act quickly that is inherent in IoT.

Intelligent and Automated – Not always the Right Idea

In this unified context, it is also important to be clear that the Vitria platform that intelligent actions does not necessarily mean automated.  While timeliness is a critical factor, human discretion is often critical to some decision or element in the decision process that flows from complex analytics.  The level of automation is entirely under the control of your organization.

Time for New Approaches

Analytics for IoT requires new ways of thinking and new approaches to systems that solve the twin challenges of complex analysis and rapid action.  On top of that, the economic stakes are often much higher than traditional analytics challenges.  Assembly line machines, power grids, health care machines, and many other IoT use cases have large economic impacts.  Now is the time for our software platforms and solutions to mature to manage, control, and preserve the economic value in those processes and applications.

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Learn more about how IoT Analytics are: