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Difference Between IoT and Big Data

Today, Internet of Things, commonly referred to simply as IoT, and Big Data are the hot buzzwords used on a daily basis in Information Technology circles. It’s almost difficult to talk about one without mentioning the other. Despite their intimate connection, they are not interrelated. Both are the future of data and by data, we mean massive volumes of data. We live in a digital era where new objects are connected to the Internet with the aim to improving people’s lives. All these devices are generative a massive volumes of data that grows exponentially and that, thanks to new technologies such as IoT, can be processed with speed that wasn’t even possible to attain until a few years ago. Many of the modern day challenges are generated by future applications where users and machines will need to collaborate in intelligent ways together. This is where technologies such as Big Data come to the picture. There is a strong connection between the two, yet, they are quite distinct.

 

What is Internet of Things (IoT)?

Internet of Things, or IoT, refers to a global network of internet connected devices or machines able to collect and exchange data. In simple terms, IoT simply are devices that collect data and send it to the Internet. IoT is a large heterogeneous collection of things, which differ from each other. IoT aims to integrate and collect information from and offer services to a diverse spectrum of physical things used in different domains. The concept of the Internet-connected devices evolved in the early 1982 with the first machine being a Coke machine at Carnegie Mellon University that would report its inventory and verify if the new drinks were cold or not. The IoT aims at provide interconnection between devices to create a smart environment in order to make machines smart enough to almost nullify human effort.

 

What is Big Data?

Every day trillions and trillion bytes of data are generated by billions of devices that are connected to the Internet; so much that 90 percent of the data in the world has been generated in the past couple of years. This massive volume of data comes from various sources; from posts to social media sites, digital pictures and videos, transaction records, payment histories, sensors used to gather climate information, or GPS signals, to name just a few. Collectively, this data is called Big Data. Analyzing and processing such massive volume of both structured and unstructured data is almost impossible using traditional software techniques. It is not merely a matter of size; Big Data is an opportunity to find insights in new and emerging types of data and content that lead to better decisions and strategic business moves.

 

Difference between IoT and Big Data

Meaning

– The Internet of Things, or IoT, is a global system of interrelated computing devices – both mechanical and digital – that are able to sense, collect, and exchange data over the Internet without any human intervention. IoT is a large heterogeneous collection of things, which differ from each other. Big Data, on the other hand, is a term that describes the large sets of data – both structured and unstructured – from a variety of sources and that is so large that it’s almost impossible to process using traditional data mining and software techniques.

Concept

– IoT is not the same as big data since neither ‘Things’ are required to collect or generate data, nor do applications need to store the data centrally in the Cloud. The IoT aims at providing interconnection between devices to create a smart environment thereby making machines smart enough to bypass human intermediaries. Big Data, as the name suggests, refers to massive volumes of data generated from a variety of sources and analyzing those data, mostly human-generated data, to support longer-duration use cases such as predictive maintenance. The concept is to find insights in new and emerging types of data and content that lead to better decisions and strategic business moves.

Time Sequencing

– Big Data involves collecting and analyzing massive volumes of mostly human-generated data but these data sets are not subjected to any kind of processing immediately for possible insights or to analyze patterns for making any kind of real-time decisions. Instead, the analysis normally occurs at a later stage and there is a lag between the time when the data is procured and when it is actually processed. IoT, on the other hand, collects, analyzes and processes data streams at real-time without any delay. IoT devices result in fast, real-time data streams to predict future insights and make control decisions in an effective manner.

IoT vs. Big Data: Comparison Chart

 

Summary of IoT vs. Big Data

In a nutshell, IoT is not the same as big data since neither ‘Things’ are required to collect or generate data, nor do applications need to store the data centrally in the Cloud. The IoT aims at providing interconnection between devices to create a smart environment and to make machines smart enough to nullify human effort. Big Data, on the other hand, involves analyzing large volumes of human-generated data to support long duration use cases such as predictive maintenance. The concept is to find insights in new and emerging types of data and content that lead to better decisions and strategic business moves.

 

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References :


[0]Image credit: https://commons.wikimedia.org/wiki/File:Big_Data_ITMI_model_with_topics.jpg

[1]Image credit: https://pixabay.com/de/illustrations/iot-internet-der-dinge-netzwerk-3337536/

[2]Bessis, Nik and Ciprian Dobre. Big Data and Internet of Things: A Roadmap for Smart Environments. Berlin, Germany: Springer, 2014. Print

[3]Dey, Nilanjan, et al. Internet of Things and Big Data Analytics Toward Next-Generation Intelligence. Berlin, Germany: Springer, 2017. Print

[4]Solanki, Vijender Kumar, et al. Handbook of IoT and Big Data. Boca Raton, Florida: CRC Press, 2019. Print

[5]Waher, Peter. Learning Internet of Things. Birmingham, United Kingdom: Packt Publishing, 2015. Print

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