Leveraging Industrial Data Ops for Sustainable Manufacturing
As the world focuses on sustainability and reducing carbon footprints, industries are seeking innovative solutions to make their manufacturing processes more environmentally friendly. In a conversation with Torey Penrod-Cambra from HighByte, we discussed how Industrial Data Ops supports sustainable manufacturing
Bringing sustainability to your industrial data architecture
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
DataOps: The Missing Link in Your Industrial Data Architecture
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
DataOps for Manufacturing: A 4-Stage Maturity Model
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
How Industrial DataOps is Shaping Industry 4.0
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,
Industrial DataOps for IIoT Scalability
Most industrial IoT difficulties are rooted in data management shortcomings. However, these challenges are not the same as those faced in a purely IT setting. For example, operational technology (OT) data is high-velocity time series and event information that many
Accelerating Industrial DataOps to optimize Data Management and IoT Scalability – a catalog of case studies
IIoT practices are having an impact, but Developers struggle to scale successful AI/ML projects. WHY? Data management is many times the culprit. Industrial OT and Business IT are not the same. For example: Business data is delivered in batches or transaction
[Research paper] The business impact of edge computing and IIoT on data management
DataOps methodology – with the goal of delivering more agile and automated approaches to data management – seeks to enable organizations to control and leverage data ranging from edge to core to cloud. DataOps is not just theoretical in its