Big Data in IoT and its Implementation

bigdata in iot and its implementation

Big Data in IoT and its Implementation

Big Data refers to a lot of data that has been accumulated by some source. It’s a present-day terminology used to refer to this big cluster of data.

Big Data in IoT refers to the collection of the huge amount of data that is collected using IoT devices. This data comprises the live/reference data being fetched from the sensors and the feedback data being collected by the actuators.

IoT deals with a wide variety of fields and types of data. This also means that these devices have to deal with diverse data daily. Some of that data might be temporary, while the other, coming as feedback, might be a permanent type of data.

The collected data is then processed and used for various corporate benefits. Just as the use of the same data varies from one business to another, the way of handling the data accumulated varies too.

The data obtained might be of high importance and relevance but can still be useless if it is not being presented and used in the right form. Often the data that is collected by these IoT devices are scattered and muzzled. 

It is not in a form that can be comprehended and understood by machines. Big Data comes into play here.

It organizes the data into discrete datasets that are ready to be processed further with various AI algorithms. More about which can be understood by reading AIoT: When Artificial Intelligence Meets the Internet of Things

So, it is evident that even if Big Data and IoT are two entirely different concepts with different objectives, they are related in the most crucial way.

In today’s scenario, Big Data drives IoT. No matter how efficient the devices are and how precise the collected data is, as seen, it would make no sense until it is processed and analyzed properly.

But, in the end, it all comes to how this is all this profitable to the businesses. Although investing in learning and implementing new technologies might seem like an expensive expenditure to businesses and companies but the profits it reaps eventually makes it all worth it!

Data patterns and trends are extremely crucial to companies, as it helps them to evaluate what works best in their interests and help them in devising new methods and work models. Numbers play a huge role in a corporate, and so does its management.

Making the services better increases reliability and, thus, proportionally impacts the ROI. Slowly the companies are taking a turn towards big data cloud storage. This helps them in minimizing the implementation cost.

big data implementation in iot

Let’s see the major areas that will significantly be impacted by the implementation of big data in IoT. 

Health Care

Health care is one of the fields that deal with a wide variety and quantity of data on a day-to-day basis. Also, noticing the patterns and taking adequate actions are extremely crucial for the patient’s well-being. 

Companies and Businesses

Wherever there are machines and patterns involved, big data and IoT come to play. IoT detects any sort of failures that might be in the cards for the machines and devices with the help of data from the sensors and feedback data from the actuators. 

Thus, helping the companies deal with the problems well in advance. 

IoT can only do it with the implementation of various AI algorithms and their umbrella components. And they require structured data, and this structured data comes from the services provided by big data. 

Thus, even if it does seem connected directly, it is being influenced indirectly by big data in IoT. 

Transportation and Electric Vehicles

Adding IoT devices is one thing and then managing the collected data is another. It gives them an edge and makes them more useful and reliable. 

Big data helps them with exactly that!

Implementing big data in IoT and using it in vehicles being used for transportation will allow people to track the vehicles, help them at the time of emergency, etc.

Using the same tech in electric vehicles makes them smart and reliable options. It makes people shift from conventional vehicles to EVs faster. Thus, helping the environment in the longer run.

It can also help EV owners to know about the health of their vehicles and the charging status.


Big data implemented in IoT can also be used for monitoring purposes. The data used for monitoring is mostly videos, pictures, and sounds. 

All this requires a lot of storage space and device capacity, and thus, shifting all the operations related to such data to the cloud is a great alternative. 

Big data helps in managing and structuring the data that’ll then make it ready to be analyzed and used.

Real-Time Data

It can also help you in dealing with real-time data and extracting meaningful insights from it. Mostly live streams and data being fetched from them needs instant filtration and monitoring.

This is where big data’s cloud implementation comes into the picture. Not only does it tackle the huge data, but it also reduces the latency created by the devices and their slow performance as well as external parameters. 

Hence, it is relevant that the implementation of big data in IoT gives it an edge over conventional IoT. 

It makes it better, faster, and more efficient. It also increases its use as it promotes convenience. Big data tools are easy to understand and can be used with very basic knowledge as well. Thus it makes the adaption smooth and desirable.

Related Posts

10 Cloud Security Risks in 2023 and Effective Solutions

In the dynamic landscape of technology, cloud computing has emerged as a transformative force, revolutionizing how businesses operate and interact with their data. However, as…
Read More

The Dynamic Fusion of DevOps and Agile Methodologies

In brand new fiercely competitive commercial enterprise panorama, groups are continuously looking for ways to maximize increase capability. Two methodologies which have received full-size traction…
Read More

Prominent DevOps Tools that You Must be Aware of in 2023

DevOps has been on the rise in recent years, and it is only getting bigger and better. With the rapid evolution of technology, DevOps has…
Read More

How to Build a Successful DevOps Culture in a Machine Learning Environment

   Image source: Taken from internet  What is DevOps Culture?  DevOps integrates activities or practices used in automation and interlinks software development processes with IT developers. For example,…
Read More

Common challenges and solutions for implementing MLOps in your organization

Common challenges and solutions for implementing MLOps in your organization      Image source: Taken from internet    The days are gone, but for what?…
Read More

A beginner’s guide to MLOps: What is it and why is it important

Machine Learning Operations (MLOps) is an emerging practice that aims to streamline the deployment, management, and monitoring of machine learning models. MLOps is an essential…
Read More


Forgotten Password?