As we move into the first few months of 2023, several emerging IT trends have become prominent blips on the radars of CIOs. Further development of AI technologies, along with a more influential role of the metaverse, represent the two most cited emerging technology trends for CIOs overseeing projects in a wide variety of industries. However, one type of technology trend receives little if any attention, but it should receive plenty of focus for CIOs that want to enhance productivity and boost the bottom line produced by their departments.

We are talking about edge computing.

Data represents the foundation for making business decisions by providing valuable insight, as well as supporting real-time management over crucial business processes. Contemporary businesses, from a giant such as Amazon to a small upstart business operating in Silicon Valley, process a considerable amount of data every day. The development of new technologies allows IT teams to gather data from sensors and IoT devices strategically placed at remote locations anywhere in the world. Issues with bandwidth coupled with unpredictable volatile network interruptions have forced CIOs to discover a new and improved way of processing vast amounts of data.

Welcome to the solution called edge computing.

An Overview of Edge Computing

Edge computing represents an architecture of distributed information technology that allows businesses to process large amounts of data on the outside edges of a network, but as close to the original source of the data as is feasible. The traditional centralized paradigm does not meet the processing needs of the rapidly growing amount of data moving through IT infrastructures. Edge computing moves a percentage of storage and computing resources outside of the centralized data center. Instead of sending data to a centralized system for processing, the data gets processed under the edge computing paradigm close to where the data originates, whether the source of the data is a smart home, retail outlet, or factory production line.

The new decentralization model is quickly changing the IT industry, as well as how businesses manage computing tasks.

What Are the Components of Edge Computing?

From interconnected automobiles to AI bots that work on factory production lines, the amount of data processed from different devices is at the highest level it has been during the digital technology era. However, most of the data is never processed and analyzed because of the overwhelming volume of data handled by centralized data centers. One example of the underutilization of data comes from a study completed by McKinsey & Company. The study analyzed the data processed from nearly 30,000 sensors placed near an offshore oil rig. The study concluded less than one percent of the data processed from the sensors to the centralized oil rig data center is currently analyzed to make business decisions.

The edge computing model relies on several types of components, with the following three forming the foundation for edge computing systems.

Edge Devices

Business use edge devices like smartphones, speakers, and watches to move data every day. These devices connect to gather and process data while interacting with IoT devices and POS systems. As AI continues to develop more advanced features, edge devices should be able to connect with robots, sensors, and vehicles.

Network Edge

A network edge is not another network that requires different infrastructure to develop. It is an extension created between computer users and the cloud. This type of component is when 5G can have an impact on computing performance in terms of both processing speed and accuracy. 5G technology delivers a powerless wireless connectivity capability to edge computing, including sending data at high speeds through cellular devices.

On-Site Infrastructure

Despite the move to decentralization that defines edge computing, the technology still requires the development of infrastructure located on-premises. The on-site infrastructure manages local systems such as intranets, as well as connecting different networks. Examples of on-site infrastructure include hubs, bridges, routers, and servers.

Bottom Line: Edge Computing Does a Better Job of Optimizing Data

Edge computing can help your organization release the potential of a vast amount of data that remains untapped in your network. You might discover new business opportunities, increase the efficiency of delivering products, and/or offer more consistent shopping experiences for your customers. Since the shopping paradigm shifted significantly during the COVID-19 pandemic, acquiring the data generated by online shoppers is one of the most important types of data for organizations to analyze.

The most effective edge computing system can help your organization enhance its performance by acquiring the capability to analyze data locally from a decentralized processing system. A properly set up edge computing system should help you immediately detect security risks, as well as manage the issues that arise when bandwidth becomes sparse. Your organization can manage workloads across all cloud computing systems, as well as from any type of externally located computing device. You should be able to deploy applications to every edge component flawlessly, as well as maintain the flexibility for adapting to rapid changes in data processing requests.

Above all, edge computing should your organization operate more securely with the utmost confidence in your network.