How Big Data influences Your IoT Solution?

Hyper-connectivity is no longer a myth. By 2025, the Internet of Things will connect more than 100 billion operational devices. This trend will be relative to the unprecedented surge in companies integrating IoT technologies with their business. This will require the management and analysis of a massive 150 trillion gigabytes of data. IoT joins the line of critical big data sources. We have reached a stage where Big data and IoT are inherently connected, and terabytes of information whizz between devices at tremendous speeds. Tapping the real potential of data generated by IoT devices is essential for achieving our digitization goals. Let us now try to explore the connection between Big Data and IoT.


How Are Big Data and IoT Connected?

The internet has emerged as a new paradigm for communication and commerce. Big Data deals with massive, diverse data sets that cannot be dealt with traditional data-processing. Products need chips and sensors along with the internet to join the internet of things. This means that big data technologies have to work harder to store, process, and analyze this sensory information. Both Big data and the IoT are distinct entities, although both can influence each other considerably.

While IoT acts as a chief source of unstructured data for Big Data, as the IoT-generated data increases at a colossal rate, conventional data storage gets exhausted. This requires advanced and innovative storage solutions to handle this massive workload. Thus, big data and IoT are both interdependent.


What Is the Nature of IoT Big Data?

IoT involves the development of products that connect to the internet. We are surrounded by devices with sensors that detect, measure, and send data in some form. As devices grow, the flow of data between devices also grows seamlessly. It is continuously streaming data in real-time. This data is specific to a particular location and time and is mostly unstructured; this means that it has to be processed before it can be used for meaningful data analysis.


How Is the Pre-Processing and Processing of Big Data Done?

IoT Big Data can be redundant and inconsistent and cannot be directly used. The Data Mining process techniques are utilized to discover knowledge from this data. This is known as Data Preprocessing. It includes cleaning, Instance selection, normalization, transformation, feature extraction, and selection, etc., to convert this data into an understandable format.

For example, suppose a sensor produces 5 values per second. We need to decide whether all 5 values need to be stored, or we can store only one useful value, say, in the form of its aggregate or average. This decision-making is crucial as it impacts the data storage capacity of an organization.

The Processing stage is where the Big Data analytics takes place. Such platforms take unstructured data collected by various IoT devices, ranging from computer devices, wireless sensors, and other gadgets and machines. This process involves streaming data as well as time-based and space-based IoT data. They aim to organize this data information into meaningful datasets, which can be used for decision-making and process optimization by companies.


How can IoT and Big Data benefit companies?


Enhanced ROI for the Businesses

IoT and big data analytics work in tandem to generate transformational results. This can massively change how businesses add value to their data by extracting maximum information to get better business insights. As more and more data storage is needed, companies switch to big data cloud storage, which is a low-cost storage measure.

Demand Surge for Edge-Computing

Both IoT and Big data work on real-time action and on-demand data. This makes Edge computing immensely popular. In simple terms, Edge computing collects and analyses data on the edge of the network rather than from centralized servers or cloud systems. This is especially beneficial for applications for logistics, large-scale manufacturing, and IoT, where the data collecting devices are numerous and highly distributed. Edge computing thus brings computing closer to the data source for faster speeds.

Predict Future Trends

IoT Big Data analytics can be extensively utilized to identify and predict future trends. This facilitates IoT analytics usage for key browse their predictive maintenance in organizations.

For example, manufacturing companies can attach IoT sensors to different machine components. This will help them track their performance based on parameters like temperature or speed. This can give deep insights into the identification of the parts that need replacement.

Improve Customer Engagement

Once again, retail businesses can use IoT and Big Data in the form of smart devices that gather information about customer behavior online without violating data privacy. For example, push notifications on their smartphones can tell how customers browse through websites or e-commerce stores.


Summing Up

The benefits of IoT and Big Data do not stop short here. Industrial IoT, in the case of industrial devices, is crucial for monitoring, collecting, exchanging, and analyzing data. Overall, IoT and Big data can converge at any point in various domains to provide new opportunities in all sectors. Big Data not only influences your IoT solutions but has a robust potential to revolutionize many aspects of business, society, and the industry as a whole.

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