Big Data and IoT: Fuelling the Future of Tech Growth (2022)
Big data and IoT are vital for the future of technology. We’ve already discussed the concept of the Internet of Things (IoT) and how this promises to revolutionize industries. A vital component of this technology is big data.
While related, both ideas stand alone as important technological concepts. To understand the relationship between them, it’s worth understanding big data first.
That’s what we’ll cover in this post: What is big data, and how does it relate to the IoT revolution?
What is Big Data?
Data is one of those terms we use daily that can have various meanings. In simple terms, it means information. Whether this is customer information, tracking metrics, performance analysis or Netflix’s viewing stats, it’s all data.
So, what is big data? Big data is simply lots of information. Rather than typical measurements, such as gigabytes, we use petabytes and terabytes. There are 1000 gigabytes in a terabyte, which should give you an idea of the sheer scale of data.
Big data is an intangible concept. We can’t touch it or see it; it simply exists. But big data is vital for the proper functioning of services. Increasingly, companies are employing machine learning and AI to capture, process, and analyze big data.
Watch this video for more information about how we define big data.
The Five Vs of Big Data
IBM, a world leader in computing tech, came up with 5 Vs to help us understand the concept of big data. They are:
Volume
As implied in the name, big data means high volumes. Theoretically speaking, the more data we have, the better we can analyze trends and develop solutions to common issues.
Velocity
Dealing with massive amounts of data means lots of time spent analyzing. This is what we mean by velocity. The faster we can collect and analyze the data, the faster we can implement solutions. AI is perfect for this because it automates the collection and analysis process.
Variety
This one is simple to understand. If we have plenty of variety in the data, then we can discover more patterns and associations.
Variability
Variability presents a challenge when dealing with big data. Greater volumes imply greater variation, which can be problematic when looking for common trends. Standardization is tricky across industries, too, particularly when using subjective data such as a medical patient expressing pain levels.
Value
This is perhaps the most important point. Big data must provide value to the user. Otherwise, it’s pointless. Having access to terabytes worth of user analytics means nothing if you don’t know what to do with it next.
What Can We Do with Big Data?
All of this points toward the question: What can we do with big data? Technically, anything.
For example, Netflix collecting viewing stats and using it to recommend new shows or decide what to produce next are both examples of big data.
Making electronic healthcare records available to all medical providers is another example of big data.
We’ll discuss some specific use-case scenarios later, but for now, it’s enough to say that the potentials for using big data are basically limitless.
Big Data and IoT: Distinct but Related
In a sense, IoT devices are part of the world of big data. If we think of big data like an ocean, IoT is the rivers that feed into it. And in this analogy, data is the water molecules that make the system.
So, big data and IoT are related – but distinct – concepts.
As we discussed in our post on automation and IoT, IoT devices run on data. That’s the point of connecting devices to one another over the internet: so they can collect, analyze, and share data. Doing so optimizes processes and reduces operating costs.
So, IoT devices run on big data. It’s the driving force behind their operation. While they might be separate concepts, they share some common goals.
Both seek to convert data into something tangible for their users. For example, tracking stock through production using IoT sensors means nothing if you don’t use the data to optimize the system (remember value?).
But, while big data and IoT are linked, that’s essentially where their similarities end.
The Differences Between Big Data and IoT
To understand the differences between big data and IoT, we can return to our previous analogy of the ocean and rivers. Both are bodies of water (the data), but they’re not the same thing at all.
Here are the key differences between big data and IoT.
1. The source of data
Generally, big data comes from human sources while IoT data comes from machine processes. For example, we’d find big data in something like your Netflix watch history. IoT data, however, is found in things like RFID sensors, asset tracking, performance optimization, and so on.
2. The purpose of data
IoT devices typically use their data to enable real-time decisions. For example, monitoring machine performance in a factory sends out alerts when a device needs repairing. Putting off this repair could prove costly, so a decision must be made quickly.
Big data, on the other hand, doesn’t lead to such real-time applications. An eCommerce seller might collect and analyze customer activity over a period of months in order to produce a targeted ad campaign to improve sales. While this will have a positive effect on the business, it doesn’t require the same timescale as the above example.
3. Site of data analysis
Due to the architecture of IoT networks, data is ideally captured, processed, and analyzed locally. This means minimal latency between devices so they can implement decisions more quickly.
As mentioned above, big data often comes from human sources and analyzes influencing human choices. For this, we don’t need to keep the data so local. For example, the eCommerce seller captures data from across the world and analyzes it on their computer. Speedy decisions aren’t as important as the latency between collection and analysis.
Common Goals Between Big Data and IoT
Even though they have differences, it’s important to stress that big data and IoT share common goals. In a sense, big data and IoT both look at improving current processes by identifying issues or trends in performance.
Also, due to the way they’re connected and their relation to cloud technology, the growth of big data and IoT are clearly linked, at least for the foreseeable future.
Use-Case Scenarios of Big Data and IoT
Although big data and IoT are fairly theoretical, it’s possible to see them in use in plenty of companies. Seeing the technology in action should help to cement the relationship between them.
Here are some of the best real-world examples of the relationship between big data and IoT.
Disneyworld
No one should be surprised that Disney jumped on the IoT bandwagon early. While its streaming service would be a good example of big data, here we’ll discuss something else: its MagicBand.
A MagicBand is an RFID-enabled wristband that functions as a ride pass, hotel room key, and payment device. You link it to your park ticket and use it to access pretty much everything in the park.
How it uses big data
Disney uses these wristbands as trackers. With the information, it can determine wait times on rides, peak park times, reduces fraud, and more. It’s almost the perfect example of big data and IoT.
UPS
UPS fitted its vehicle fleet with telematics devices that transmit real-time data to its servers. This isn’t a new concept. In fact, it started this back in 2010. What is new is UPS’s ORION system.
How it uses big data
ORION stands for On-Road Integrated Optimization and Navigation system. The name alone should answer the question. It uses algorithms and data tracking metrics (big data and IoT) to optimize routes, reduce fuel consumption, and reduce operating costs.
TIVE
TIVE provides customers with real-time shipment tracking information. While this alone isn’t new, TIVE’s approach to the type of shipments it tracks is novel. For example, it specializes in high-value assets and chemical shipments.
How it uses big data
TIVE fits its goods with a range of sensors depending on the product. For example, a chemicals shipment would have temperature and damage sensors. It then feeds this information to customers and provides alerts for things like port delays and unexpected damage.
The Climate Corporation
The Climate Corporation developed something called FieldView. It allows users to collect, store, and upload data about their fields. Also, users connect their farming devices using IoT devices to upload data in real time.
How it uses big data
The company collects data to analyze farming trends, soil quality, crop maintenance, and more. It recently partnered with AgEagle, a drone company, to provide aerial support for farms based on this data.
Conclusion – The Future of Data
Big data promises to be the most important asset of the coming tech revolution. Many look to AI, machine learning, and even IoT as the next big thing. But none would be possible without big data.
So, big data and IoT might be related and share common goals, but big data is the ocean that gives life to all the rivers of technology.
