HighByte Blog
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Time to read: 7 minutes  Posted by Torey Penrod-Cambra 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  Posted by John Harrington 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. Time to read: 6 minutes  Posted by Torey Penrod-Cambra When it comes to data collection, who are you really serving?
That objective often gets lost amid the OT/IT alignment discussions. Anyone who has embarked on a digital transformation project is likely familiar with the data silos that exist between their OT and IT departments. But we don’t spend enough time talking about how to make that data usable for the line of business. Our line of business colleagues (and their systems of record) are the ultimate customer. The use of IoT-enabled devices is increasing the availability of operational data. IDC has projected there will be 41.6 billion IoT devices in the field generating 79.4 zettabytes of data by 2025. These devices include machines, sensors, and cameras as well as industrial tools. To truly make that data usable, we need to merge this data with information from other systems and provide context for line of business users. In an industrial environment, these users include quality, maintenance, engineering, R&D, regulatory, and product management. Time to read: 8 minutes  Posted by John Harrington How much time do you spend cleaning data?
If your factory is like most connected operations, you probably have tons of raw data streaming from connected devices to existing enterprise systems, bespoke databases, and a cloud data lake. This architecture often leads to inconsistent or even unusable data for several reasons. We know the Cloud is a key tool for digital transformation. It provides the scalability and storage capacity you need to collect and interpret vast amounts of data coming from the operations level. However, by nature, cloud platforms are IT-focused tools. They structure data differently than operational systems, which means IT must spend a lot of time cleaning the data before it can be used. And if the data moves directly to different enterprise systems, multiple teams across the organization will clean the data independently, leading to different versions of the truth. |
