Due to the pandemic, most of us work remotely, and businesses start to leverage digital platforms and services most aggressively. Initially, data consumption drastically increases, and the data collected from billions of internet of things (IoT) devices is stored in the cloud for faster data processing. When it comes to financial services, global traders need to take real-time decisions based on market shifts. If any lag occurs in data computation, it seriously results in the loss of money. It is also applicable to healthcare industries even a slight delay in processing data would lead to a person’s death. While processing the bulk data stored in the cloud mightn’t be able to handle or process the whole data at a time, it delays. To tackle this problem, that’s where edge computing comes into play. Read our latest case study by clicking here!
What is Edge Computing? Edge Computing architecture is referred to as the data processing at the network level to decrease the overall latency on cloud and data center resources by reducing demands. However, due to the increased use of edge devices, there is an unexpected growth in data generated and collected. By the end of 2025, almost 75% of the data will be created out of the central data centers. Do you know? 90% of the data which enterprises collect will never be used. One of the primary reasons for the growth of edge computing is its higher efficiency. Every day, the volume of loT data keeps on increasing while processing also takes place at the edge. However, through the loT devices, a massive amount of data is collected, and only the critical information is extracted and used. In this process, the processing takes closer to