Big Data

Building Your IT Infrastructure for the Internet of Things

MAY 01, 2015

Handling a Big Data infrastructure is one of the biggest challenges that today’s businesses are facing – in fact, as noted in a recent discussion by Dell, it’s only going to get worse as time goes by. Fortunately, there are several things a business can do to build a Big Data infrastructure that’s ready for the future.

The Power of Automation for Big Data Infrastructure

Automation has always been one of the driving forces of the internet – indeed, marketing automation has helped countless companies reach far larger audiences than they could have ever handled otherwise. Even search engines are becoming increasingly selective about what they display.

As far as Big Data infrastructure goes, the goal is simple: if it can be automated, it should be. Reducing the amount of stress that’s placed on the network will allow it to run more quickly and efficiently, something that’s critical in a world where instant answers are the norm.

Selectively Acquiring Information

How much data is too much? The ideals of Big Data make sense on paper – by having a large sample size, it’s easier to filter data and pull meaningful information from it. On the other hand, as explained by Anton Chuvakin, companies sometimes find out they’re collecting so much data that they can’t even store it. This is one of the major problems with Big Data Infrastructure – it needs to be able to scale at almost frightening speeds in order to keep up, and companies who can’t do that will quickly find themselves losing the information they paid so much to acquire.

The solution? More efficient acquisition of information. There is no need to collect literally every piece of information that a Big Data Infrastructure can scan – only the data that’s actually meaningful should be stored.

One major issue exists with this approach: Companies don’t always recognize the information they’ll need until well after they begin collecting it. That’s why each company needs to take the time to analyze the different types of data they’re able to collect and ask if each part is worth keeping. Expert Tip: When going through this process, compare every metric to every other metric and ask if there’s something of value there. Many of the most important pieces of data only come from a mix of metrics, so don’t discard one of them because it’s worthless by itself.

Modifying the Business Model

This is a part of setting up their Big Data infrastructure that many companies are hesitant to talk about – after all, employees often wonder if a new business model would displace them and ruin what they’ve worked so hard to achieve, and that’s a very understandable reaction. However, businesses can’t afford to ignore the opportunities that an improved Big Data infrastructure provides.

Vincent Granville recently provided a list of areas that are likely to benefit from Big Data analytics over the next decade – and any business can benefit from studying this list. For example, #13 discusses improved ways of classifying text, and companies who are quick on the uptake will be looking for these categories to emerge and asking how they can manage their use of them. #9 focuses on continued improvements in search technology, and someone involved with the Big Data infrastructure will have to work on ensuring that relevant information is put in the right places.

The lesson to take away from this is that business models will need to be adjusted – probably several times – as the Internet of Things grows and society’s expectations for businesses change. Companies who prepare for this shakeup will fare far better than those that don’t.

For more information on how to build your IT infrastructure for the Internet of Things, get in touch with our experts here at Trace3. We’d love to talk to you and help you get your organization squared away.

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