Follow Datanami:
March 2, 2021

ScaleOut Software Joins Digital Twin Consortium to Share Streaming Analytics Expertise

BELLEVUE, Wash., March 2, 2021 — ScaleOut Software today announced that it has joined Digital Twin Consortium to help define and advance the use of digital twin technologies across various industries.

“We are excited to join the Digital Twin Consortium,” said Dr. William L. Bain, founder, and CEO of ScaleOut Software. “We believe that digital twins offer great promise across numerous industries from telematics to IIoT, healthcare, physical security and eCommerce. They can dramatically improve situational awareness for managers of live systems spanning thousands or even millions of data sources, and we are delighted to help raise awareness of the concept of harnessing digital twins for streaming analytics via the Consortium.”

As defined by Digital Twin Consortium, the digital twin concept encompasses use cases for both product lifecycle management (PLM), where the idea originated, and for real-time streaming analytics for live systems. ScaleOut Software’s real-time digital twin technology represents the latter approach and adopts this concept for streaming analytics. The company’s “real-time digital twin” software architecture for streaming analytics across industries provides more informed decision making in the moment for applications that track thousands of data sources.

Real-time digital twins create a “model” of each individual data source as they track the specific characteristics relevant for the goals of streaming analytics, such as detecting anomalous conditions or predicting failures. This generalization of the modeling concept allows digital twins to analyze not only physical devices but also a wide array of data sources that would not be typically considered, such as ecommerce shoppers for a recommendation system.

“We welcome ScaleOut Software to Digital Twin Consortium,” said Executive Director, Dr. Richard Soley. “Their knowledge of real-time digital twin software and streaming analytics will be very valuable to our members as we work together to advance digital twin technologies.”

Harnessing the Digital Twin Model

ScaleOut Software’s streaming analytics platform leverages the digital twin concept by associating a software component, called a “real-time digital twin,” with every data source to analyze the incoming telemetry from that data source. Large systems, such as trucking fleets or access control systems, often require thousands of data sources to be simultaneously monitored. Each real-time digital twin maintains dynamic state information that assists in predictive analytics and other use cases. This enables deeper inferencing about the evolving state of each data source than otherwise possible.

When run on a scalable, in-memory computing platform, real-time digital twins dramatically increase the amount of analysis that can be performed as telemetry arrives, and they avoid the delays incurred by offline, big-data analytics. The in-memory platform can simultaneously host thousands or even millions of digital twins to ensure predictable response times, and it can continuously aggregate state information for immediate visualization.

Benefits of Real-Time Digital Twins for Streaming Analytics

Real-time digital twins:

  • Provide Immediate, Contextual Insights: Real-time digital twins allow the telemetry from a large population of data sources to be immediately and independently tracked, analyzed, and filtered, while making use of dynamically evolving contextual information. They enable feedback and alerts to be generated within a few milliseconds.
  • Aggregate Insights to Identify Trends and Issues: Real-time digital twins maintain dynamic state information that can be aggregated and visualized to identify important trends or issues within seconds. This capability dramatically boosts overall situational awareness for managers of live systems.
  • Simplify Development and Deployment: Real-time digital twins offer a compelling technique for simplifying application code and shortening design time. The digital twin model can be implemented using well understood, standard, object-oriented techniques that encapsulate analytics code and state information. This enables fast development and agility to meet evolving requirements.

For more information, please visit www.scaleoutsoftware.com.

About ScaleOut Software

Founded in 2003, ScaleOut Software develops leading-edge software that delivers scalable, highly available, in-memory computing and streaming analytics technologies to a wide range of industries. ScaleOut Software’s in-memory computing platform enables operational intelligence by storing, updating, and analyzing fast-changing, live data so that businesses can capture perishable opportunities before the moment is lost. It has offices in Bellevue, Washington and Beaverton, Oregon.


Source: ScaleOut Software

Datanami