The Internet of Things and real-time analytics

Joseph Schumpeter, one of my favorite economists, coined the term "creative destruction" to describe the way in which innovation disrupts how things are done, and in the process, gives rise to new companies and new ways of operating. What's been called the Internet of Things -- the rapidly proliferating connection of all devices, sensors, machines and people -- is set to create disruption on a huge scale. This ups the ante significantly for analytics and real-time computing.

The driverless car is an excellent example as a disruptive innovation that impacts both consumers and businesses. For instance, when driverless cars become common, not only will they change commuters' experiences, they are expected to lessen the incidence of traffic accidents, improve the density of road use, smooth subsequent planning for maintenance, ease long-term planning for other transportation systems such as light rail, and much more. What makes all of this possible? The Internet of Things' flow of data between the cars, street lights, people, radios, cellphones, etc, And the real-time analytics that makes the important real-time decisions for the driverless cars.

It is only human nature. Once consumers and businesses have a taste of the Internet of Things and real-time analytics benefits, they'll want more of it. In fact, it has been said that along with the influx of data, by 2017 more than 50 percent of analytics implementations will make use of event data streams generated from instrumented machines, applications, and/or individuals. How can companies keep up with this real-time analytics demand? By changing how analytics is currently done to fit the new digital need, including:

  • Analytics of vast amounts of data will increasingly be performed in the cloud or on devices themselves.
  • New ways of distributing analytics will be used. Currently, a lot of analytics applications are large and run on servers. In the next few years we'll start seeing more and more limited and targeted "apps" running on small sensors embedded in devices. These will have to be updated remotely, as it will be too expensive to distribute the analytics any other way.
  • The analytics conducted on servers and laptops today will start being performed on sensors and chips, which will allow decisions to be made far from where the code was originally written. For example, the personal devices that monitor and analyze individuals' health or the success - or otherwise - of their workout offer real time, minute-to-minute performance insights and suggestions, telling their wearer how to achieve the fitness goals they've set. We'll increasingly see those immediate insights and recommendations extended to many more areas of life and business.

Important to note is that for businesses to jump into the Internet of Things and truly take advantage of the real-time analytics benefits it can offer, organizations must look beyond the existing data and analytics and approach a larger strategy to enable success. Elements of the strategy should involve test and learn pilots, a data governance program, and a technology infrastructure that supports mobile and big data.

If you think that the world of driverless cars, robots carrying out maintenance in hazardous locations like oilrigs, or advertising that reads and responds to individuals' unique facial expressions sound like science fiction, it's time to think again. These are all developments happening today and they're prompting a new exciting phase in analytics that needs to be addressed now. Those that embrace the data will be more likely to be surfing on top of the wave of creative destruction, instead of having it crash down on top of them.

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