The Benefits and Challenges of Analyzing Data at the Edge
All new technologies bring with them the potential for progress and change but are always accompanied by associated challenges. Those challenges now affect the landscape in which these new technologies operate. Learning how to navigate them while simultaneously leveraging the positive aspects of these new technologies is what allows room for tremendous growth and progress.
The differences between cloud computing and edge computing are significant. For those that are implementing edge computing technologies, understanding the benefits, as well as the challenges that await, is the first step to the successful adoption of new and powerful technology.
What are the Benefits of Edge Computing?
Real-Time Responsiveness
One of the most notable benefits of edge computing is a real-time data processing and how quickly raw data can be transformed into actionable specifics, used in everyday operations.
Reducing Latency
Waiting for data to return from a centralized, big data center can cost you in today’s business climate. Less demand on the network leads to reduced latency which opens possibilities for better customer experiences and reduces the amount of lost time or data that a company will experience. According to a recent interview with industry experts on Edge computing experts, NTT said “Using private 5G with edge computing can fundamentally change our experience of technology. By delivering faster downloads, less latency, and improved efficiency across networks, this combination can make our devices work together better. Additionally, it allows mobile devices to process data natively, allowing for real-time analysis and machine-learning capabilities.”
Data Analysis
Analyzing data used to be considered the domain of cloud data centers because of the storage and processing power they have. No more! Edge computing allows users to determine what information should be saved by analyzing the data and only sending the pertinent information to the cloud centers.
Reduce Overall Costs
Overall, operating edge computing is a cost-saving measure. While there are up-front costs to installing and managing edge devices, being able to keep the data from connected devices closer to the site where that data is created and analyzing it there will save users money by reducing network usage and cloud storage.
AI and Machine Learning Applications
Edge computing is key to maximizing AI and machine learning programs. These applications need real-time analytics and data analysis while simultaneously having low-latency internet connections for optimum operations. Edge computing can account for and provide for all those factors.
User Experience
User experience, for many industries, is what makes or breaks their success. Edge computing allows businesses to do things better, faster, and more effectively than their competition, creating a user experience that keeps customers coming back for more.
What are the Challenges of Edge Computing?
Complexity
Setting up and running an effective edge computing system isn’t easy. It is a complex system that is more difficult to operate than a traditional cloud-based infrastructure because you have multiple devices interacting with each other across different interfaces.
Security
IoT devices, while they are great at producing and transmitting edge computing data, are not particularly secure. They are simple devices that can be interfered with and potentially can be used as an avenue for cyber-attack.
Upfront Cost
While it is a more cost-effective option, the upfront cost of setting up an edge computing system can be daunting. There are devices and software to be installed, as well as training for staff to operate and work with the edge computing systems.
Analyzing Data at the Edge
Businesses will continue to adopt edge computing as the technology matures and works its way into most parts of the economy. Understanding the benefits and preparing for the challenges will give companies the edge they need to compete in the marketplace of tomorrow.
