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    Four Ways Edge Computing Helps in Digital Transformation

    Edge computing can be the connection that supercharges potential business outcomes in the case of many advanced capabilities, such as machine learning or IoT.  

    Four Ways Edge Computing Helps in Digital Transformation

    By

    Apac CIOOutlook | Friday, February 26, 2021

    Stay ahead of the industry with exclusive feature stories on the top companies, expert insights and the latest news delivered straight to your inbox. Subscribe today.

    Edge computing can be the connection that supercharges potential business outcomes in the case of many advanced capabilities, such as machine learning or IoT.

    FREMONT, CA: As the enterprise’s evolving edge computing technologies gain traction, how they converge with digital transformation strategies is becoming more apparent. Usually, digital transformation focuses on enabling improved goods, services, experience, or business models. Data is at the center of such transformation, but fundamental changes are also only necessary if the company can make substantial changes in how information is obtained, moved, stored, or processed.

    Here are four ways how edge computing helps with digital transformation:

    Support for Latency-Sensitive Applications

    The most common application of edge computing is in streaming high-definition media, from online gaming to augmented reality (AR) applications for service technicians to next-generation sports stadiums’ streaming of real-time videos.

    In life-or-death situations, Edge computing can also speed things up. Instead of relying on centralized cloud services, healthcare organizations can locally store and process data. As a consequence, for quicker diagnosis or treatment, clinicians may get more immediate access to critical medical data such as MRI or CT scans or ambulance or ER information.

    Arranging and Securing Distributed Assets and Devices

    Companies in the energy and utility sector can see value in deploying edge capabilities to allow operational efficiency interventions in real-time. Managing multiple legacy assets from various manufacturers may entail running an oil rig.

    An asynchronous data model approach has been adopted by many IoT sensors used in warehouses, factories, regions, and automobiles.​

    Real-Time Visibility and Responsiveness

    In stores and regional warehouses, retailers are increasingly implementing edge systems. For greater supply chain visibility and logistics oversight, consumer packaged goods firms can also harness the intersection of edge computing and DT.

    Enhanced User Experiences

    The COVID-19 pandemic fueled the need to help remote workplaces and habitats better. But the events of the past year have put a heavy burden on the infrastructure of global networks. In certain ways, the integration of edge-optimized tools will provide staff, partners, and clients with improved experiences.

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