Data, data, data. Data is everywhere. We are surrounded by data. With IoT becoming a reality, the amounts of data created has increased multifold and going into the future, the rate at which data is generated is only going to increase. But what matters most is what we do with this data and how it can be used to better our existence. Data mining, data processing and data computing is integral to any business for better insights and in making crucial business decisions.
Primitive times saw this data computing being done at an onsite server. Later, cloud technologies saw this data being processed remotely in the cloud far off from the data generation site. Though Cloud Computing is very beneficial, real-time data processing improving user experiences, reducing costs and optimising business logistics, is the need of the hour.
This is where Edge Computing can help.
Edge Computing brings certain aspects of data processing, data computing and data storage near to the devices where the data is generated in microdata centres rather than depending on data centres located far away. Retaining and processing data at the site or on the edge aids in quicker real-time analysis and faster response-time for businesses. Edge Computing is a complete game changer in how data is processed and analysed by businesses.
Let’s now have a quick look at the challenges posed during the adoption of Edge Computing.
Though, Edge Computing architecture provides a unique solution for analysing and processing data to provide response to real-life scenarios in real-time, it also presents its own set of unique challenges:
Edge computing has a myriad of benefits and a huge number of use cases where it can be applied due its unique feature of data processing at the edge. With the number of devices being connected to IoT increasing and the integration of Artificial Intelligence and Machine Learning, edge computing is here for the long haul.
Reduced Latency: Since the data is being processed locally, there is no requirement to transfer to the cloud. This significantly reduces the time required for analysing data and responding to the user.
End-User Satisfaction: The integration of AI, ML, NLP, AR and VR gives the user real-time responses with an immersive experience, leading to optimal end-user experience.
Less Load, Better Performance: As the data is processed close to the data collection source, the load on the servers and networks, required to transfer data to the cloud is lessened. This improves the performance of all your enterprise applications.
Superior Security: As the data is distributed among the edge network and devices instead of being concentrated at a single source, it remarkably reduces the chances of a cyber-attack compromising the entire network or accessing the complete data. All you need to do is block off the affected network or device and the attack can be contained.
Efficiently Connected: The edge architecture is designed such that the data remains and processes near to the end-user. This reduces connectivity problems affecting data processing even in the most remote places. This also lessens the chances of a remote connection issue affecting the entire network. If such a case arises, data can be redirected and the end-user will still not be affected.
Scalable: More devices can be added to the edge to accommodate the growing needs of your business as and when required. This is very significant as the data from IoT will continue to grow with the adoption of 5G connections and Wi-Fi 6.
Conclusively, Gartner predicts that by 2023, almost 75% of the data processing will be conducted at the edge and the global edge computing market is set to cross $13 bn.
Effectively, Edge Is the Future and it is here to stay.
If you are looking to refine or upgrade your IT infrastructure or are thinking of investing in any of the associated technologies, contact us. Our experienced and talented architects and developers can provide you with a comprehensive, cost-effective solution that aligns with your business goals, increases ROI and boosts growth.