Everyone’s talking of the Internet of Things (IoT) and the impact it’s started to make even on day to day lives. Yet, more than anything, it’s also becoming increasingly clear that analysis of the IoT data will be the differentiator between those who simply collect data and those who “use” it to drive their businesses.
Enterprises that will use IoT analysis will see themselves implementing faster customer services than their rivals, as well as add new amounts of additional yields.
That said, it’s clear that the IoT analytics will require a well-thought out strategy on part of the Enterprise. Unlike the other, modern-day streams of data analytics, this branch is slightly more complicated. The primary reason – the humungous amounts of streaming data that is/will be generated and analysed, in real time.
For now, one way forward looks like collecting information and analysing the same on the smart device itself. In other terms – Edge Analytics. Utilising the smartness of the device and its low cost computational power will help run analytics on the device itself or close to the source instead of the hub itself. As close to the edge of the system seems to be the answer, for now. The Big Data analysis than comes out of this “mini analysis” can then be done in the Cloud in real time.
So, in such a model, Enterprises will have to tackle many questions, including – how much of information has to be captured by the sensors, initially? How much has to be analysed and how much forwarded to a core location for further analysis? The analytics team will have to develop rule-based models that can determine all of this including how the gateway will handle data.
A note of caution - Edge Analytics may not be for every business and an initial feasibility test may have to be done to understand whether your business needs one or not.