To make industrial data actionable, evolve your data historian with an AIoT strategy

In my last article, I wrote about how industrial organizations, in the rush to implement new technologies like AI, the cloud, and the Industrial IoT, have found themselves with a technology stack packed with legacy, plumbed-together, on-premises solutions. The result is an environment with not only multiple siloed data sources, each storing, formatting, and securing data in their own unique ways, but also an equally siloed approach to understanding how to leverage that data into something actionable across the enterprise. Domain experts become not just go-to sources for understanding a certain process or workflow, but the only people with insight and meaningful context into different data sets tracked or generated by different sources.

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