On the Edge of Tech: How Edge Computing is Changing Business Intelligence
Here’s a fact: over 90% of ALL data ever created was generated in the last two years alone. Every time a Google search is sent (almost 70,000 per second), an email is received (over 2.7 million per second), or a social media post is shared, astronomical amounts of data continue to stockpile. It’s estimated that by 2020 there will be 726 billion digital payment transactions annually—almost 2 billion per day!
Add the proliferation of IoT devices and it’s no wonder that the constant flood of data can choke legacy systems and networks. Thankfully, the development of edge computing can enable organizations to accelerate their processing speeds and more efficiently analyze meaningful data. Operations analytics, remote asset monitoring, process monitoring, employee monitoring, and workplace safety can all benefit from edge computing’s improved security as well as reduced costs, latency, and network traffic.
What is Edge?
Edge computing is a shift in architecture where intelligence is pushed from the cloud to the edge, thereby enabling localized analysis and decision-making. Edge computing deployments are ideal for numerous reasons. For one, since analytics and data gathering occur at the data source, latency is significantly reduced. Data can be analyzed in near-real time, as opposed to traveling across long routes to data centers or the cloud to be processed. By immediately dissecting the data at its source, edge ensures that only valuable data is sent over the network. The saved bandwidth frees up network capacity, prevents bottle-necks, and ultimately results in saved time and money.
Originally, edge computing was developed to ingest, store, filter, and send data to cloud systems. Now, as the technology evolves, edge systems are beginning to pack more storage, processing, and analytic power, giving them the ability to act on data at the machine site.
The Impact of Edge on Business Modernization
Edge computing is critical to the development of new technologies that rely on immediate and relevant data. More and more companies are beginning to capitalize on data and analytics to drive the growth of their organization. The auto industry is a prime example. While still in the developmental stages, autonomous vehicles are slated to be available to the consumer market as soon as 2020. These cars create massive amounts of location and movement data that must be processed and shared with neighboring vehicles in real time. Edge has made self-driving cars more capable of analyzing and finding patterns in sensor data while simultaneously increasing the speed that data is available, thereby enabling autonomous vehicles to make faster, more accurate decisions on the road.
Similarly, the development of 5G, and its ability to provide speeds 10 times faster than 4G, means the potential for increased processing power for a variety of IoT devices, not just smartphones and tablets. The increased volume of data at a faster speed will drive the deployment of edge computing systems. It’s predicted that as telecom providers build 5G into their networks, they’ll also add micro-data centers located at 5G towers solely for the purpose of edge computing. These data centers will have direct access to a gateway into the telecom provider’s network, which could connect to a public cloud. With the assistance of edge computing, the 5G infrastructure market is estimated to be worth $33.72 billion by 2026.
Potential Implications of Edge
As the use of edge computing rises, so does the debate on a few key aspects of the technology. Many in the community are torn about whether or not edge is secure. Some developer communities believe that edge devices may be more susceptible to security breaches, thereby posing even greater risks. On the flipside, security may be heightened because data is now closer to the source. By sending less data to the cloud or data center, the risk is lower in the event those environments are compromised.
Another controversial element to edge computing is the fact that only a subset of data is processed and analyzed. Much of the raw data is discarded, potentially resulting in missing insights. While developers are able to access the “most important” data from other locations, the perceived less important information is kept onsite at the edge location.
How Edge Computing is Changing Business Intelligence
The future of edge computing is bright. Entire industries are evolving around the ability to streamline data and quickly convert it into actionable insights. As the amount of daily data generated continues to grow, it’s evident that edge computing will be a crucial component in digital transformation, the future of analytics, and the growth of data-driven industries.
Is it time to start thinking about how edge computing will impact your business?
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