The Intersection of Big Data and IoT

Big data is defined as extremely large, complex data sets used for performing analytics that reveal patterns in behavior and interactions, typically through the everyday use of technology. The goal is to identify trends and any other notable associations present in the data.

The Internet of Things, on the other hand, is a vehicle of big data—the things that are collecting and sending that data. Big data is where IoT information goes, lives and gets measured. The Internet of Things is an origin point for big data (although there are others, such as machine-generated data).

The tech world today is summed up in one word: connected. If your device isn't connected already, it will be, and big data and IoT are the major perpetuators of that connectivity.

Most people have heard the all-pervading statistic: The number of devices that connect to the internet will rise astronomically over the next several years, with some estimates predicting it will be over 50 billion by 2020. That's the premise behind IoT—billions of devices will be connected to the internet for the sole purpose of being able to provide instantaneous feedback, data and general information, for both the end user and the companies that are collecting that data for internal and external purposes.

Examples of IoT objects that are generating and sending user data:

• Refrigerators
• Garage doors
• Traffic lights
• Vehicles
• Light bulbs

Since several new smart refrigerators have been released recently, let's use them as an example. Consider a newly developed smart refrigerator that includes a 20-inch LED touchscreen monitor and internal cameras that allow you to look in your refrigerator remotely, enables the capability of ordering groceries and sends maintenance notifications—so if your lightbulb is about to burn out, both you and the manufacturer are notified.

Today, most refrigerators aren't connected to the internet. But in the not so distant future, not only are we going to connect them to the internet, but we're also going to connect them back to the manufacturer, who is going to gather data points stemming from questions such as:

• How many times a day do you open your refrigerator door?
• How long are the doors open when you do open them?
• Which foods do you run out of most frequently?

We'll send extensive amounts of data without even knowing that we're generating it; that's where big data comes in.

Think of big data as massively large data sets that are used to look for patterns, trends and any kind of a data association between one behavior to another, specifically around human interactions. The intents are to first, sell the data, and second, to develop products that better fit consumer lifestyles.

Today's technology decision makers and stakeholders in product planning and development are paying attention to big data because their competition is also paying attention. Most businesses want the data for internal use, and hopefully, to create a revenue stream in the near future. The more information a manufacturer or vendor has about a product, the more they can refine and develop its functionality and features to meet the needs of consumers.

Two different practices, both changing the world
A common misconception around big data and IoT is that they're the same thing, or that one cannot exist without the other, which isn't true. Big data has been around longer than the concept of the IoT, and just because you have a device that talks to the internet doesn't necessarily mean that it's collecting or transmitting data.

For instance, you can install garage doors that can be controlled via the internet. If your children leave the house and forget to close the garage door, you're notified through your mobile device, and have the ability to shut the garage door from anywhere with internet access. However, it's not likely that the manufacturer of that capability is collecting data on how many times your garage door goes up and down—that's not useful information. But it's still an IoT device because its functionality depends on being connected to the internet, and it is through the internet that you can choose to open or close your garage doors without being home.

While big data has been around for a considerable amount of time, it is still growing and developing. Where IoT is concerned, there's a definite, steady increase in the number of connected devices. Both big data and IoT are in their infancy compared to where these initiatives will stand five to ten years from now.

We're only scratching the surface of both big data and IoT's impact in the future. We at Flexential predict that their evolution is paving the way for the next Googlesque tech success story—the next generation's Steve Jobs and Bill Gates will be the people who develop big data and IoT applications that offer functionality and data insight that we don't even imagine today.

Objects that no one ever thought would be connected to the internet will be, and products will be designed based on any and every kind of demographic you can imagine. The world is going to begin collecting exponentially more data, analyzing it and selling it back to manufacturers to ultimately create the perfect product, whether it's a washing machine, camera or stoplight.

Storing an abundance of information
Given the volume of information generated as a result of big data and IoT, some of the key questions for big data and IoT players are: “Where do we store the data?,” “What will we use to analyze it?” and “How long do we have to keep it?”

There are so many different ways to approach big data analytics, and infinite functions for which different organizations are using it. But the storage issue is the same for everyone, with a lot of variables to consider. If you are new to the big data arena, consulting an experienced provider, particularly one seasoned in security, is a safe path to follow.

Generally speaking, big data is not something you're likely to store in a public cloud environment. More often than not, big data means big compute, with lots of storage and lots of bandwidth. A large colocation environment is the most popular strategy for storing big data; parking your infrastructure in a reliable data center facility allows your business to forego the issues of power and connectivity, but lets you maintain your own environment.

Leveraging cloud infrastructure as a service (IaaS) is certainly something that many organizations look into. However, knowing that not all cloud hosting services are created equally, consumers of big data need to understand the demands of their environments before placing these workloads just anywhere.

Flexential offers a number of flexible colocation solutions to meet the demands of data-intensive environments. For a comprehensive consultation, or to talk through your big data plans, visit www.flexential.com or call (888) 552-FLEX.