The rising importance of data could be argued as one of the most important side effects of the internet revolution. Through advertising sales and return on investment metrics, the traditional sponsorship and advertising models have been thrown out of the window in favor of cold hard figures and data that can be acted upon, such as profiles, activities, email addresses and phone numbers.
Even if you’re not selling a product to a specific audience, the data produced from everyday interactions with servers through the Internet of Things can produce insights that can change the way businesses go about their processes.
This data is cultivated within these IoT devices, placed on the edge of the network, feeding businesses’ analytic platforms up in the cloud with the information they lust for. Within manufacturing, for example, machines in assembly can detect problems or even future issues reading from sensor data, in order to feed it back to the analytics platform for the business to act on.
According to research published in September from Global Industry Analysts, the global edge computing market is set to be worth over $17 billion by 2026. That presents a huge opportunity for businesses to take advantage of the innovations that that kind of market growth will bring, and an even bigger opportunity for those who can provide solutions at the edge.
Analyzing on the Edge
There are clearly a lot of insights to be found on the edge, however feeding that information back to a cloud platform and then analyzing it can be a slow and intensive process.
The insights that can be gained from the information on the edge allow reaction in real-time, and feed analytic engines, that allow to take decisions on data predicting the future, that reduce spending, find new opportunities or alter the model of the business, to take a couple of examples.
Therefore, having the information fully formed before the arrival at the cloud and then aggregate information from many edge points in the cloud can be the difference between getting to market quicker and beating the competition or having to fight for every customer. That information doesn’t necessarily have to be regarding a product, a process or service that is being provided, it can in fact be analyzing how employees are working, when they are busiest and how they manage their time. Let’s take manufacturing for example.
Companies within the sector want to be able to analyze and detect changes in their production lines before a failure occurs. Edge computing helps by bringing the processing and storage of data closer to the equipment. This enables IoT sensors to monitor machine health with low latencies and perform analytics in real-time.
Embrace the Edge
According to IBM, by 2025 every connected person in the world will have at least one digital data interaction every 18 seconds, and there will be even more devices driven interaction. The sheer amount of data that will need to be processed requires some analytics at source, with a clever, selected sync to the cloud only. By analyzing data on the edge of your network, Smart IoT devices can use artificial intelligence to detect the best data sets, disregarding the numbers that are not useful, to feedback actionable insights that businesses can use.
This is a trend that is happening too. In the same research, IBM heard how 91% of the organizations they surveyed had plans to implement some form of edge computing within 5 years. There is no sitting on the fence anymore - heavy compute on the edge of networks has now proved to have applications in multiple industries including manufacturing, sports and fitness and farming, but not always connected to the cloud
For enterprises, embracing data on the edge of networks can look a bit banaler. However, such insights also need to be monitored to enhance productivity. In a current landscape where ‘Zoom Fatigue’ has become a commonplace obstacle for organizations to overcome, being able to talk to employees about when they work, how they organize their day and that 12 meetings in one day might not be the best way to contribute to the business.
Enterprises can also take advantage of intelligent edge integrations within their back-end infrastructure, a key growth area since the pandemic. At the Local Data Center, Compute and Gateway, edge devices have become a necessity in the face of growing demands on IT teams and dwindling budgets.
For example, Local Data Center managers are looking for solutions that will allow them to monitor and manage their stack that they can quickly install. Similarly, the Gateway edge solutions businesses want to take advantage of are set-and-forget solutions, allowing IT professionals to have peace of mind that access is being security granted to those who should have it, whilst still allowing a level of remote management when necessary.
As with many innovations within the technology industry, adoption can be stifled by not knowing where to start. But the start of businesses’ edge journey can be with smaller solutions that use artificial intelligence to make IT teams easier. From there enterprises can roll out solutions throughout different departments, in order to ensure a productive workforce.
For years the AI and edge markets have been awash with complex use cases for manufacturing and small devices packed with sensors, which certainly is where it can be useful. But behind the heavy machinery and complex language, the average business can utilize the edge in a way that is not daunting but in fact makes sense, is simple to operate and deploy, and does not take a long time to set up.
That is because, at the end of the day, edge computing is all about harnessing data, making sense of it and making decisions that will make you more efficient. By embracing AI on the edge, enterprises stand to save money, find new opportunities, win more customers and improve their customer loyalty rates as they can transform that information and pass it on in the form of USPs, guarantees or simply advise as to how to make their products and business better.
Christian Lutz, Founder and President, Crate.io