Edge Analytics is a form of analytics that performs in real time and in effect, reduces and refines the amount of overall data. You could say Edge Analytics acts like a funnel, filtering out the least useful information, leaving you with the most important to analyse further.
If you’d like a more complex sounding definition then you might like this one from Tech Target: “Edge analytics is an approach to data collection and analysis in which an automated analytical computation is performed on data at a sensor, network switch or other device instead of waiting for the data to be sent back to a centralized data store.”
A good example can be found from Bernard Marr’s Forbes article:
“A simple example would be a massive scale CCTV security system, with perhaps thousands or tens of thousands of cameras covering a large area. It’s likely that 99.9% of the footage captured by the cameras will be of no use for the job it’s supposed to be doing – e.g. detecting intruders. Hours and hours of still footage is likely to be captured for every second of useful video. So what’s the point of all of that data being streamed in real-time across your network, generating expense as well as possible compliance burdens?”
Algorithms are now being developed that can analyse data as it comes in and the benefits of this are obvious. It will save labour time and help organisations make the right decisions quicker. The time saved could see a company gain a competitive advantage by acting ahead of their competitors.
Is Edge Analytics the future?
In short, it should be. Edge Analytics ultimately saves vital time in the decision-making process for companies and as technology continues to evolve and difference between success and failure becomes even smaller, it will be advantageous for companies to fully utilise Edge Analytics.
Of course it will be more beneficial in some industries more than others but it certainly looks like Edge Analytics has a part to play in the future of the growing Data and Analytics industry.