Edge computing brings great opportunities to build scale and create value from exponential data growth in the market – with IoT, 5G and AI only accelerating this growth.
First, what does edge computing mean in this context? One could say it is interaction between people, machines and business processes. Another way to define it is the placement of computing and intelligence as close as possible to digital touchpoints, whether that means intelligent production lines, autonomous vehicles or smart buildings. And all this is happening outside of cloud and traditional data centers.
Data growth is a shared issue among all of these elements. IoT and 5G are driving more and more connected devices that generate more data, while the rise of AI increases the expectation to get more value from that ever-growing data. It is estimated that within the next few years, most enterprise data will be created and processed outside of data centers or clouds.
But why? Partly because of the need for lower latency. Partly because of data growth exceeding the available bandwidth. Partly because of time-criticality and the need for greater autonomy, or simply security. Usually it is a combination of these factors.
Across the Nordics, we see many prime use cases emerging that are the driving the need for edge computing. In the industrial sector, predictive maintenance, precision farming, quality control assessment and fleet management are good examples. Tracking assets, predicting and preventing leaks or water quality are key use cases in the infrastructure and utilities sector. We see numerous other examples in logistics and across consumer services. And the potential applications are constantly growing.
The maturity of these edge use cases also drives the need for new kinds of solutions and architectures with increasing autonomy at their edges, ultimately enabling fully autonomous and self-adapting systems. This presents challenges for CIOs, starting with figuring out how to deal with the ever-expanding myriad of technologies combined with new requirements for networks (latency and so on). Furthermore, data and analytics increasingly live outside of core enterprise applications and processes, which necessitates an end-to-end security approach, from connected devices all the way through to cloud services and back to the enterprise applications.
We help our customers to design, build and run edge solutions all the way to IoT end-devices, with extensive data, cloud and analytics advisory and application services. Read more from our website.