Author: John Harrington

  /  Articles posted by John Harrington
About The Author

John Harrington is the Chief Product Officer at HighByte, focused on product management, customer and partner success, and go-to-market strategy. John is passionate about delivering technology that improves productivity and safety in manufacturing and industrial environments. He has spent his 25-year career both delivering software to manufacturers and working for manufacturers in operations roles. This experience has given him a unique perspective on how suppliers and end users each play an integral role in implementing new technology solutions. John has a Master of Business Administration from Babson College and a Bachelor of Science in Mechanical Engineering from Worcester Polytechnic Institute.

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The Unified Namespace (UNS) is among the fastest-growing data architecture patterns for Industry 4.0, promising easy publish-subscribe access to hierarchically structured industrial data. The UNS is often defined as a consolidated, abstracted structure by which all business applications can consume

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Have you ever watched a press conference when a room full of reporters bark questions at the same time? Typically, the media event host will call on a particular reporter to repeat the question and then move on to the

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DataOps is a new category of software solutions that address the data architecture needs of industrial companies as they adopt Industry 4.0, Digital Transformation, and Smart Manufacturing. DataOps solutions perform data contextualization and standardization and provide secure data flow to

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The promise of Industry 4.0 has many manufacturing leaders thinking big. They envision a future in which real-time access to data opens the door to unprecedented levels of operational flexibility, predictability, and business improvement. For many, early-stage wins often lead

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Industry 4.0 adopters in factories around the world recognize that industrial data is gold. More users and systems want access to this data in real time to convert it into valuable information they can act on to predict machine failure,