The Internet of Things and Really, Really Big Data

Stephen DeAngelis

August 11, 2016

The Internet of Things (IoT) is going to generate a massive amount of data. How much? “Annual global IP traffic will pass the zettabyte (1000 exabytes) threshold by the end of 2016,” reports Víctor Vilas (@victorvilasmatz), Business Development Manager Europe for AndSoft, “and will reach 2 zettabytes per year by 2019.”[1] What Vilas is really saying is that the era of Big Data is over. Why? Because calling a zettabyte of data “big” doesn’t really conjure up the right picture of just how really, really big a zettabyte of data is. The following graphic provides you with some indication of how large a zettabyte really is.

An infographic produced by Cisco and included in Vilas’ article notes, “1 exabyte amounts to 36,000 years of HD-TV video, or the equivalent of streaming the entire Netflix catalog 3,177 times. … It would take over 5 years to watch the amount of video that [crossed] global networks every second in 2015.” If that isn’t illustrative enough, the infographic notes, “If the 11oz coffee on your desk equals one gigabyte, a zettabyte would have the same volume as the Great Wall of China.” That, my friend, is really, really big data. Brian Buntz (@brian_buntz), writes, “There is a ton of hype surrounding the Internet of Things. But the common assumption that the IoT is progressing at a linear rate is wrong.”[2] He asserts, “The IoT is about shift into ludicrous mode.” Buntz reports that Cisco’s Rowan Trollope (@rowantrollope) told participants at the Cisco Live conference, “One of the biggest mistakes you could make now is to underestimate the Internet of Things.” David Booth, CEO at BackOffice Associates, adds, “We are at the tipping point of the Internet of Things (IoT) — where physical devices across the globe are consuming and creating data to drive a continuously connected world.”[3] Booth continues:

“It was not a huge leap for the industry to realize that an IoT global network of continuously connected devices would mean that data would not only be created at geometric rates, but that it would become one of the most valuable commodities in the world. And although there are many new start-up companies storing, analyzing and integrating massive lakes of big data created from the IoT, not many have actually considered how the IoT will transform how organizations think and implement data quality and information governance.”

Clearly, analyzing the amount of data that is going to be created by the Internet of Things is going to require new, advanced analytic techniques. Fortunately, the area of artificial intelligence (and, especially, cognitive computing) are maturing rapidly. This is no coincidence. Artificial intelligence systems require massive amounts of data to draw from in order to learn; which means, there is a symbiotic relationship between data and artificial intelligence. With so much data being generated, companies need to understand what they want to do with data and ensure they have access to the right data. Kevin Kalish, IoT Domain Lead at SAS, told Asha Barbaschow (@ashabeeeee), “The view of big data in IoT is that it is more a commodity and that sometimes can lead businesses to the desire to become a bit of a data hoarder.”[4] Kalish believes data hoarding can be a problem because, unless a company can find a way to monetize their data cache, it can become an economic drain on a business. “The misconception,” he notes, “is that storage is a commodity and big data will solve these problems; but, the volumes and the costs are quickly becoming unsustainable.” That’s why companies need to understand their real data requirements. Barbaschow adds:

“In the future, Kalish believes there will be sensors in every imaginable place; that such a smart world is going to significantly change how an individual and an organisation should approach innovation, as well as how it connects to its customers and manages it day-to-day. According to the self-confessed IoT evangelist, having more data attributes is not necessarily a good thing when an organisation is not 100 percent sure how it is going to accumulate and manage the data.”

Despite potential challenges associated with the Internet of Things, I agree with Trollope that ignoring the IoT is not an option and companies will do so at their own peril. Andy Daecher (@adaecher), a principal for Technology Strategy & Architecture, and Robert Schmid (@roberteschmid), Chief IoT Technologist at Deloitte Consulting LLP, assert, “Like a wildfire racing across a dry prairie, the Internet of Things (IoT) is expanding rapidly and relentlessly.”[5] They continue:

“As IoT grows, so do the volumes of data it generates. Globally, the data created by IoT devices in 2019 will be 269 times greater than the data being transmitted to data centers from end-user devices and 49 times higher than total data center traffic. Even as businesses, government agencies, and other pioneering organizations take initial steps to implement IoT’s component parts — sensors, devices, software, connectivity — they run the risk of being overwhelmed by the sheer magnitude of the digital data generated by connected devices. Many will focus narrowly on passive monitoring of operational areas that have been historically ‘off the grid’ or visible only through aggregated, batch-driven glimpses. But to fully explore IoT’s potential, companies should think big, start small, and then scale fast.”

At Enterra Solutions®, we call this a “crawl, walk, run” approach. This kind of approach helps ensure that you are collecting the right data for the right reasons to gain the right insights. Daecher and Schmid add, “The value that IoT brings lies in the information it creates. It has powerful potential for boosting analytics efforts. Strategically deployed, analytics can help organizations translate IoT’s digital data into meaningful insights that can be used to develop new products, offerings, and business models. IoT can provide a line of sight into the world outside company walls, and help strategists and decision-makers understand their customers, products, and markets more clearly. And IoT can drive so much more — including opportunities to integrate and automate business processes in ways never before possible.” Ensuring that you get a symphony rather than a cacophony of noise requires a platform that can act as a conductor. Cognitive computing systems offer just such a platform. Cognitive computing systems can gather and analyze both structured and unstructured data, eliminating the data silos that characterize industrial age enterprises, and they can mine data for actionable insights that make companies more efficient. And, as Daecher and Schmid note, when you add in the Internet of Things a company can do so much more. They conclude, “The sheer scope of IoT carries countless implications for business, both finite and abstract. To sidestep such distractions, focus on solving real business problems by creating bounded business scenarios with deliberate, measurable value.”

Footnotes
[1] Víctor Vilas, “Welcome to the era zettabyte thanks to the internet of things,” AndSoft Blog, 21 September 2015.
[2] Brian Buntz, “The IoT Is About to Shift into Ludicrous Mode,” Internet of Things Institute, 12 July 2016.
[3] David Booth, “Harnessing the Data Tipping Point of IoT,” Information Management, 18 July 2016.
[4] Asha Barbaschow, “Big data is a big miss when it comes to IoT: SAS,” ZDNet, 26 May 2016.
[5] Andy Daecher and Robert Schmid, “Internet of Things: From Sensing to Doing,” The Wall Street Journal, 11 May 2016.