When it comes to modern big data systems and related cloud computing platforms, you’d think that storage capacity, processing power and network bandwidth would be the primary elements of an efficient system. It’s becoming increasingly clear, however, that’s not the case, especially as more businesses emphasize data acceleration.
Data acceleration essentially refers to the rate or speed at which large troves of data can be ingested, analyzed, processed, organized and converted to actionable insights. Speeding up these processes, as you might expect, is the acceleration aspect. More importantly, because there is so much that goes into an efficient data system, it’s more of a concept that involves all hardware, software and related tools.
 
By focusing on data acceleration as a whole, platform developers and network engineers can deliver targeted solutions to improve power, performance and efficiency of these platforms.
By focusing on data acceleration as a whole, platform developers and network engineers can deliver targeted solutions to improve power, performance and efficiency of these platforms. Simply installing a faster server or enabling wider network pathways are just a couple examples of how you can improve a system in the short-term.
However, they don’t offer the real benefits that a truly optimized and efficient platform can. It’s all about operating in the right environment and under the right conditions to create an optimally functioning data facilitation system.
It’s remarkably similar to edge computing — on the surface, anyway. Data is analyzed and handled closer to the source in the edge, to maximize security but also reliability, speed and performance. Data acceleration uses similar principles, except the data in question is not local — it’s still remote. Unique hardware and systems are enabled to mitigate packet loss and latency issues.
Why Does Data Acceleration Matter so Much?
According to BDO, “During the period 2014-2020, the percentage of U.S. small

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