Big Data and the Internet of Things Are Two Separate Practice Areas—but They Affect Each Other
What is Big Data?
Big data can be defined as extremely large, complex data sets data sets used for performing analytics to reveal patterns in behavior and interactions, typically through the everyday use of technology. The goal is to identify trends and any kind of notable association.
What is the Internet of Things?
The Internet of Things, or IoT, is a vehicle of big data—the things that are collecting and sending that data. Big data is where IoT information goes, lives and is measured against. The Internet of Things is an origin of big data (although there are others, such as machine-generated data, for example).
Big Data, the Internet of Things and the State of the Technology Realm
The tech world today can be summed up in one word: connected. If your device isn’t connected already, it will be, and big data and IoT are major perpetuators of that connectivity.
Most people have heard the all-pervading statistic: the amount of devices that connect to the internet will rise astronomically over the next several years, however, estimates differ greatly from as low as 6.4 Billion by the end of 2016 to over 50 Billion by 2020. The actual amount of connected devices may be unknown but what is known is that the total amount of devices gathering and providing information will be staggering. That’s the premise behind IoT—billions of devices are going to 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:
- Garage doors
- Traffic lights
- Light bulbs
Since several new smart refrigerators have been released by various manufacturers recently, let’s use this 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, you and the manufacturer will be notified.
Today, our refrigerators, for the most part, 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 be sending extensive amounts of data without even knowing that we’re sending it; that’s where big data comes in.
Think of big data as massively large data sets that are going to be 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:
#1—Sell the data
#2—Develop better products that fit consumer lifestyles
Today’s technology decision makers and stakeholders who have any involvement 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 Practice Areas, 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 Internet of Things. They’re often talked about in the same context, which is why people are commonly confusing them.
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 doors, you’ll be notified through your mobile device, and have the ability to shut the garage doors 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 doors go up and down—that’s not useful information. However, it’s still an IoT device because its functionality depends on being connected to the Internet, and it is through the use of 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 Peak 10 predict that their evolution is paving the way for the next Google-esque kind of 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 have the answers for 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 to ideally fit the needs and preferences of consumers. 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 stop light.
Storing an Abundance of Information
Given the volume of information being generated as a result of big data and IoT, one of the practical questions for big data and IoT players is “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; there are a lot of variables to consider. If you are new to the big data arena, consulting an experienced provider, particularly one who is 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, lots of storage and lots of bandwidth in turn, a large colocation environment is the 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 continue to maintain your own environment. Leveraging cloud infrastructure as a service (IaaS) is certainly something that people look into, however, knowing that not all cloud IaaS is created equally, consumers of big data need to know the demands of their environments before putting these workloads just anywhere. Peak 10 offers a number of flexible colocation solutions to meet the demands of data-intensive environments. For a comprehensive consultation, or to talk through planning for your big data plans, visit www.peak10.com or call (866) 473-2510.
Dull, T. (n.d.). Big data and the Internet of Things: Two sides of the same coin? Retrieved July 27, 2016, from http://www.sas.com/en_ph/insights/articles/big-data/big-data-and-iot-two-sides-of-the-same-coin.html