Modernizing Industries with an IoT-Powered Digital Twin

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Click to learn more about author Shawn Ryan.

With a plethora of new technologies and innovations infiltrating industries, companies are scrambling to develop cutting-edge digital initiatives and incorporate more holistic, data-driven results into their business strategies. One specific technology gaining traction in multiple verticals is the Internet of Things, or IoT. In the context of data, IoT is instrumental in elevating digitally driven business initiatives by providing organizations with a more comprehensive view of operations via new data points in previously uncharted territories.

To take the concept of IoT one step further, modern enterprises are now paying close attention to data generated via IoT sensors – especially enterprises relying on complex machinery or technology processes that do not already have built-in internet connectivity. This implementation of IoT sensors on otherwise “dumb” objects enables the creation of a “digital twin,” or a virtually modeled counterpart to a physical entity. For example, a manufacturing company can place IoT sensors on specific parts of a machine, providing the data needed to create a comprehensive, computerized model of the machine. This digital twin will then provide relevant, real-time information to an enterprise, such as the condition of machine parts and current temperatures, as well as enable the use of Predictive Analytics to determine the length of a product’s lifecycle. The power of the digital twin also lies in the remote nature of the virtual twin that allows users to monitor operations from afar, which is especially game-changing when considering the use of digital twins in industries like oil and gas and aerospace.

The implications of the digital twin reflect the evolving nature of data in our increasingly innovative business landscape. By leveraging the latest data technologies, enterprises can up level business strategies and their industries overall by crafting predictive experiences based on real-time data, in comparison to how we view data today. These predictive experiences will be the driving force behind key business differentiators, such as the ability to provide ultimate customer experiences that can anticipate real-time user issues and provide timely solutions. Although IoT remains in its earliest stages, enterprises and business leaders must adapt their way of thinking to accommodate a more predictive, efficient and complex data reality.

Preparing for the Technology of the Future

It is crucial for enterprises to future-proof their Data Management and process strategies in the present day in order to realize the full potential of emerging data-reliant technologies of the future, including IoT, Machine Learning and the creation of digital twins. Organizations must start by building a proper data foundation that is scalable and has the ability to be flexible and all-inclusive. Modern data platforms and related solutions – such as application programming interfaces (APIs), or the building blocks behind apps – already enable organizations to streamline and weave data into a comprehensive and real-time view of operations. Ultimately, a well-built data foundation will be the future of the enterprise, and will help organizations stay ahead of the technology curve when the next data revolution becomes a reality.

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