If you think that human beings generate a great deal of information these days, you are right. At the same time, though, as the Internet of Things (IoT) approaches, you ain’t seen nothin’ yet.
More than ever, people are quick to bandy about the term Big Data. There’s plenty more to say about the matter (hence my rationale for scribing Too Big to Ignore in 2012), but perhaps it’s best to think about Big Data in the following simple framework: people and machines.
Let me elaborate. People actively generate a great deal of data, something that social media has certainly intensified over the past decade. Today, we frequently tweet, share videos of our pets, take and post photos on Instagram and Facebook, write blog posts, and the like. To be sure, we’re talking about a boatload of data, an amount that grows every day. Still, to view Big Data exclusively through this active, human-centered lens would be incomplete.
Rise of the Machines
Machines passively generate enormous troves of data.
Machines passively generate enormous troves of data. Yes, I’m talking about the burgeoning world of the IoT. A few examples will help clarify what has surely become an off-repeated business buzz phrase. Farmers will be able to easily monitor and improve in-season crop health. Progressive Insurance’s Snapshot program (formerly coined “Pay as You Drive” [PAYD]) allows drivers to lower their rates by installing a device that tracks their driving behavior. Airplane sensors provide critical in-flight information.
Of course, none of these scenarios happens without cheap, connected sensors and sophisticated networks that can support them. Simply collecting and/or storing new data sources and streams, however, isn’t enough. Mere data collection is sufficient but not necessary for success. The companies that will reap the true benefits of the IoT will do more. They will ask fundamental questions of these exciting new data sources. They include:
- How can we make sense of these new streams?
- Are we willing to go wherever the data takes us—even if that ultimately challenges long-held assumptions about how things work? Are we willing to embrace true data discovery?
- Does our organization run the right applications to analyze and interpret this data? What about the right employees?
- How can our employees embrace machine learning to make better business decisions?
It’s tough to overstate the potential benefits and opportunities of the IoT. I can’t predict the future, but it’s safe to say that the true winners of the IoT will be the ones that get in early on the action. This means taking part in critical discussions about forthcoming standards. What’s more, it requires preparing for inevitable change and adopting new technologies.
What say you?
IBM sponsored this post.