HighByte Blog
Read company updates and our technology viewpoints here.
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Read company updates and our technology viewpoints here.
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Time to read: 6 minutes ![]() Ever since the first release of HighByte Intelligence Hub in 2020, HighByte has developed the solution to meet the industrial data integration needs of today’s industrial customers and tomorrow’s market requirements. The first version of the Intelligence Hub was a client-based application that collected and published contextualized data to any consuming system. As Industry 4.0 leaders began to integrate more systems and assets into their ecosystems, data consumers needed better data visibility and access. The consumers wanted to be able to see all available information, so they could access exactly what they needed. To deliver this visibility and access, we embedded an MQTT broker into the Intelligence Hub, giving administrators the necessary tools to build a Unified Namespace (UNS) that would allow consumers to easily subscribe to the information they desired. With changing needs in mind, in May 2023, we took the next step in the evolution of the Intelligence Hub, adding the ability to request data on-demand through the Intelligence Hub with a built-in REST Data Server. This addition allows users to request time series, transactional, or master data from systems through a single, simple API. Time to read: 7 minutes ![]() You don’t have to agree with environmental policies to know that sustainability is a part of business and life today. Supply chain partners, regulators, customers, and investors are demanding more environmental accountability from manufacturers—and with good cause. According to the International Energy Agency, the manufacturing and power sectors account for 63% of energy-related CO2 emissions worldwide. Progress depends largely upon their success. Thankfully, manufacturing has come a long way since the third industrial revolution that saw a rise in automation and productivity without much consideration for environmental impact. The fourth industrial revolution, or Industry 4.0, has given manufacturers more insight into their operational efficiencies. Network-connected assets provide a real-time lens into performance metrics that go hand-in-hand with more sustainable production. Still, this level of connectedness presents a new challenge: How to manage data more efficiently. Time to read: 7 minutes ![]() For the past several months, 55 beta testers in 13 countries have been kicking the tires on HighByte Intelligence Hub version 3.0 and generously providing their feedback. Today, I’m excited to announce this major release is now available. Version 3.0 is a step change for the Intelligence Hub and for the Industrial DataOps market. It raises the bar for what a DataOps solution can be at Enterprise scale. It introduces a powerful new Pipelines builder to curate complex data pipelines. It makes the often-vague concept of the Unified Namespace (UNS) tangible and achievable with an embedded MQTT broker—reducing additional software, cost, and administration overhead for our customers. I sat down with HighByte Chief Product Officer John Harrington to talk about some of these advancements available in Version 3.0, including Pipelines. His thoughts are below. I also provide insights from our partner Goodtech, a deep dive on the embedded broker, a review of new project management capabilities, and more. Time to read: 6 minutes ![]() 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 next person in the room. Without some ground rules, an actual conversation couldn’t take place. No one could hear the questions being asked, and few would get any answers. Unfortunately, this same scenario often occurs with industrial data. With so much operational technology (OT) data generated on any given day, manufacturers risk losing critical information in the sea of “data noise” coming from their systems or having to expend vast resources to clean that data in the cloud. |
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