The better part of the past decade has been characterized by businesses pivoting from their IT assets and instead opting for the service-based models of the cloud. This switch has provided companies with various innovation routes, allowing them to generate and leverage vast data sets despite local storage and processing limitations.
In addition, CIOs and IT heads gravitated towards the scalability and flexibility advantages provided by the cloud, leveraging the advanced security, cost savings and better collaboration to map a faster way to market. However, more tech departments are looking towards adopting edge computing for better performance and more secure digital asset management.
Savvy enterprises have adopted a two-pronged approach that marries conventional cloud solutions and edge computing. Charting such a course allows businesses to take advantage of the security and manageability of on-premises systems while also leaning on public cloud resources from a service provider.
On the edge of the cloud
The pandemic-borne business uncertainty forced several companies to reassess their decision-making approach, allowing them to react to market forces appropriately. Executives leveraged powerful technologies like artificial intelligence and machine learning to anticipate market changes and respond accordingly.
However, business data analysis can be a bit more challenging when using cloud computing because data has to travel to a central location for analysis. Unfortunately, the prevailing business environment requires faster analysis for insight generation.
As such, edge computing has become a more attractive strategy because it allows businesses to interact comprehensively with data at its source. As a result, enterprises have embraced data science and AI-enabled technologies to glean insights from new data.
In 2018, only ten percent of business data was processed and analyzed outside the data center – evidence of business trust in cloud computing. However, Gartner predicts that the proportion of extra-network business data processing will increase to 75 percent by 2025.
Here’s what businesses obtain from edge computing:
- Low latency data processing compared to cloud computing due to a reduced need for massive data troves to be transferred to the data center for analysis.
- Low latency also promotes more accurate AI modeling due to richer and more complete data sets at the network edge.
- More robust data sovereignty due to localized data sourcing, analysis and processing
- Edge-centric data processing doesn’t always require an internet connection, unlike cloud computing which necessitates the connection for data access. This means edge business solutions can be distributed over a more expansive network.
- Processing and storing data over local area networks is significantly less costly due to the limited amount of data businesses send to the cloud.
Nevertheless, IT heads can adopt an edge-cloud hybrid approach to enterprise data management efforts.
Concurrent use of edge computing and conventional cloud solutions
CIOs can manage the enterprise’s IT infrastructure with a hybrid strategy comprising edge computing and traditional cloud solutions. After all, both approaches provide distinct features, the combined benefit of which offsets their individual shortcomings.
For instance, conventional cloud solutions are ideal if a given business function produces dynamic workloads. Alternatively, edge computing is suitable for sizeable workloads too costly to send to the cloud.
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