The concept of the Internet of Things isn’t nearly as futuristic as some might have you believe, in fact its dead simple. Take an object, stick on some sensors and Wi-Fi capability, and there you have it – a device. These devices are rapidly taking root, and as their number grows exponentially, so does the amount of data they produce.

Consider what Cisco has to say about it. The “Internet of Everything,” as it likes to call IoT, is set to become a $544 billion industry in this year alone, while by 2020 its predicted that there’ll be some 24 billion connected devices in the world. And all of these connected ‘things’ will be using and sending data – lots and lots of it. As InfoWorld’s Bob Violino notes, soon we’ll be dealing with “Big Data like you’ve never seen before.”

For CIOs and IT managers, it’s kind of tempting to just think it’ll be okay to leave the management of these devices to each department within your organization, but there are a number of reasons why that would be a foolish strategy. The ‘thing’ about the Internet of Things is, each of these newly connected devices needs to be treated more like a mini-appliance – each one will create streams of data that need to be managed, and each one will need to be secured from threats. That’s without considering all of the performance, stress tests and scalability problems that’ll likely crop up along the way.

In a recent IT Pro article, research firm Gartner contends that IT leaders are the Internet of Things “natural entry point”, and says that CIOs and other IT professionals should look at how to manage these devices now, before adoption becomes too widespread:

“By understanding the various classes of devices that will likely populate the Internet of Things, the CIO will be well-placed to spot additional opportunities or see similarities that business colleagues may overlook.”

Mega Big Data

One of the biggest stumbling blocks will be dealing with all of the data that comes via the Internet of Things. The problem is that this won’t just be ordinary data, nor even Big Data – what we’ll have is Mega Big Data. With all of these new sensor-loaded devices and wearable tech in the enterprise, we’re going to see absolutely crazy amounts of data being produced, all of which will have to be sorted, integrated, analzyed and managed. For IT leaders, the challenge will be to come up with a data analytics platform that’s capable of handling all of this Mega Big Data, and to implement a scalable infrastructure that can support it.

The issue is taken up by Duek Chung, co-founder and chief marketing officer of Parature, in a Harvard Business Review blog post. In his post, Chung argues that a specialized data analytics platform for the Internet of Things will become a must-have for enterprises:

“The fact that millions of devices will soon be Wi-Fi enabled will cause a flood of user data for companies to sift through. Businesses can use this data to understand where issues are happening on their products, how frequently, and best resolutions — but only if they have the means to analyze it.”

Luckily for us, vendors are already rushing to provide predictive analytics solutions for the Internet of Things. Companies like IBM and GE have already come up with products to help IT leaders manage the unique challenges posed by Big Data in the Internet of Things.

Chung continues:

“This type of predictive analytics solutions will be the norm, and companies will need to incorporate tools that will inform and improve customer service engagement on all of their devices.”

But before we even get that far, we’re going to need to find some way of collecting all of that IoT Big Data, then we’re going to need a way to integrate, model and distribute it. According to IBM’s Big Data wiz James Kobielus, the most important criteria here will be something he likes to call “operational economies of scale,” which can be best achieved through cloud-based technologies:

“From a planning perspective, you should start with the assumption that all IoT analytic functions benefit from the scale economies of centralization, unless one or both of the following criteria—functional scope and real-time speed—make distributed deployment more appropriate.”

For IT leaders, the challenges posed by Big Data in the Internet of Things are no joke. By the end of this decade practically every little thing – no matter how disposable, specialized or mundane it may be – will be churning out endless streams of data tidbits, and the time has come to start thinking about what we’re going to do with it all.