Element brings semantic data platform to Azure Digital Twin cloud service

Element brings semantic data platform to Azure Digital Twin cloud service

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Element Analytics Inc., maker of a semantic data platform for use in industrial settings, today announced the availability of its Unify data management platform on Microsoft Corp.’s Azure Digital Twins cloud service.

A digital twin is a software rendering of a physical asset that matches the characteristics exactly for the purpose of running simulations, testing performance and modeling improvements. Users can create digital twins from computer-aided design software and connect them to other data sources to model their performance and much lower cost than building and testing prototypes.

Element Chief Executive Andy Bane described his company’s Unify product as “a semantic data layer that sits between all the sources of [information technology and operational technology] data you need to structure,” he said. “We help companies organize their operational data and bring structure that makes it easy to work with and scale. The category hasn’t emerged yet. Some people call us data operations and some call us a data fabric.”

Element has connectors that bring data in from source systems to create a modeling layer that developers can use to build digital twins more easily without having to unify data from disparate sources. The platform can also detect changes in the underlying data sources and automatically update the model.

“We shrink the complexity developers face by over 90%,” Bane said. “Instead of 1 million data points to look at, they can look at 10,000 but have access to all 1 million.”

For example, Bane said, if a failed pump is replaced with one that has three times the number of sensor tags, Unify can automatically detect and represent the additional data points. “We have a no-code approach to building the data pipelines,” he said. “Once they’re turned on the data will propagate and you can bring it in or detect changes.”

Element Unify’s integration with Azure Digital Twins enables users to accelerate the deployment of digital twin models through the use of templates and attributes which are translated to the telemetry, properties, components and relationships expressed in the Digital Twins Definition Language or DTDL.

Synchronization between the Azure Digital Twins and the Unify semantic model simplifies governance and maintenance and existing, Azure Digital twins models can be imported to Unify for reuse and governance in the Unify semantic data model and later saved in a template library. The Element data model can also be imported into Microsoft Power BI, PowerApps, Azure Data Lake Storage, Azure Blob Storage and other cloud services for analytics.

Image: Element

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