Putting it simply, Edge Analytics is the collection, processing and analyzing of data to a sensor, a network switch or any other connected device. Edge Analytics is data analytics in real-time and on site where data collection is taking place. It could be diagnostic, descriptive or predictive analysis.
According to Gartner, edge analytics will enable users to leverage data analytics ‘beyond those of traditional business insights’ and will increase the efficiency by spotlighting the smallest detail with exceptional precision of analysis and relevancy.
Edge analytics is a model or an approach to data collection and analysis in which, instead of waiting for the data to be sent back to the centralized data store, an automated analytical computation is performed on data at a sensor, network switch or any other device.
WHY USE EDGE ANALYTICS- Edge analytics is just not another gimmicky term invented to make our lives more difficult. It is highly popular because of the few key benefits it provides. They are as follows:
The excessive adoption of internet of things (IoT) universally resulted the significant increase on edge analytics application.Edge analytics prove to be very useful in a number of industries and sectors. Let’s start with ana example. Suppose, a device that controls the temperature of a refrigerator could detect a change which can be quite dangerous and can damage the products in seconds, in the internal temperature of the refrigerator. Here, delay couldn’t be afforded.
But if the data were required to go back to the central server, be processed and parsed and then relayed back to the sensor, the goods inside the fridge would undoubtedly spoil. But with Edge analytics, this problem could be solved in a jiffy with the help of the sensor which relays the problem and implements a solution instantly.
Despite the few possible challenges of implementation, the edge analytics model does not fail to present a long-lasting trend which enables the users to obtain valuable insights in real-time, bring structure to unstructured content and feed relevant data to the cognitive-oriented systems.
The market players are investing in storage and networking gear at the edge for a perfect facilitation of work process and strategic exploration of advanced analytic capabilities without fails. It helps them to make the most of the collected data.
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