At the CES 2015, I was fascinated by all sorts of possible applications of IoT – socks with sensors, mattresses with sensors, smart watches, smart everything – it seems like a scene in sci-fi movies has just come true. People are eager to learn more about what’s happening around them and now they can.
While I was at there I attended a talk given by David Pogue – he is awesome. He pointed out that the prevalence of smartphone is the key to the realization of the phenomenon called “Quantified Self.” I agreed with him. Smart phones play a vital role as a hub where all our personal data converge and present, seamlessly. The fact that you carry your smartphone around all the time and that the screen size perfectly reveals all the information results in a catalyst for wearable devices, IoT or what we like to call it, Intelligence of Things.
It’s all relevant; Big Data, IoT, Wearable, Cloud Computing… While most data is uploaded to the cloud, the client devices are generally powerful enough that the computing can be decentralized. That said, small data (client side) and big data (server side) form an eco-system where small data triggers the knowledge base cultivated by big data and does the predictive analysis and decision making in a timely manner. Furthermore, your smartphone gathers versatile data and is able to analyze cross-app data to personalize your application settings. For example, what about optimizing navigation based on my physical condition? Or how about suggesting the best route according to my health along with the weather? These individual data records might be small, but collectively they enrich the content of analysis and contribute some amazing value. We at BigObject really appreciate this context of Big Data.
Marc Andreessen once said, “I think we are all underestimating the impact of aggregated big data across many domains of human behavior, surfaced by smartphone apps.” For us here at BigObject, the next big thing in big data is to find out a methodology that can link multiple data sources together and identify the meaningful connections between that data. Most importantly it must be responsive enough to deliver actionable insight and simple enough for people to adopt. That is the key to fulfill a connected world.
Originally posted on Data Science Central