Two of the most popular trends which affect industries and businesses in the present days are the Internet of Things and Big Data. However, it should note that while IoT platform is often correlated with Big Data it is actually a different concept though it is closely interconnected with it. This post will discuss the differences, interfaces, and contributions each technology type offers to todays business and social solutions.
Understanding IoT and Big Data
To better appreciate how the two different terms work, it is necessary to define both first.
IoT (Internet of Things) gives an affiliation of relating machines – sensors, devices, gadgets and other tangible objects which link and exchange data over the internet. They could range from быть every day appliances, industrial tools, or tools used in the medical field, smart city technologies among others. IoT systems are based on IoT platforms that serves for the organization of connectivity with devices, data acquisition, and analysis.
While Big Data, as the second term, means the large volumes of highly structured and unstructured data set produced at the high velocity and varying in terms of variety. Big Data platforms allow the storage, processing and analysis of this data for the generation of insightful Information. It usually originates from different sources such as IoT devices, social media platforms, transactions systems, and more, and thus acts as an enabler of data driven decisions.
Main Difference Between, IoT and Big Data
Purpose and Functionality
IoT is mostly about the generation and transmission of actual-time data. In allows devices to communicate with their surroundings through data gathered from sensors sending them through the internet for analysis or a command. The concept of IoT is to make living spaces such as homes and cities or business entities like factories and healthcare, intelligent.
Big Data is a concept that involves collection and analysis of this data from multiple sources. To summarize it in a simple way, Big data 90% comes from connected devices of IoT, however, other data sources include business transactions, social media activities, emails and videos. Big Data platforms are rather orient to working with real-time data flows, but they can also use the historical data as input.
Data Types
Most IoT applications create mostly real time data, they are often little in size but the data generation rate is quite high. This data is frequently collected directly and frequent preprocessing is often necessary before it is in a form well-suit to expanded analysis.
Big Data on the other hand deals with a large volume of organized or unstructured and semi-structured data. Besides real time sensor data from IoT devices, it handles text, images, videos, audio files, and log data. Consequently, Big Data platforms need high specialised solutions for addressing this type of variety and complexity in information.
Architecture and Infrastructure
The IoT infrastructure partially consists of IoT platform that act as the middle point between the devices and the main systems in the IoT networks. Such applications offer device control, performance monitoring, and data forwardings, making communication between devices and cloud services continuous.
Big Data platforms on the other hand employs distributed computing frameworks such as Hadoop or Apache Spark for storing of big data. These systems are design to work on the large sets of data across clusters of machines in an organization. The architecture is design for high level parallel processing as well as advanced analysis.
Data Processing
IoT essentially operates on real time data and the most valuable asset is response time and immediately actionable insights. IoT devices can notify the relevant users, cause some actions, and even perform analytics based on the values sensed by the connected sensors.
Big Data platforms on the other hand are mean for ETL or stream processing, which enables data analytics to happen over time and scale. Big Data’s goal remains strategic — it is concerned with such things as the longterm patterns, conducting in-depth analysis on historical as well as real-time data, and building models for the future. Although, IoT data necessitates timely decisions, Big Data analysis is generally more intricate, time-consuming but provides sophisticated results.
Use Cases and Applications
IoT Use Cases: IoT has been applied in various industries including smart homes, smart city, industries or Industrial IoT, farming, medical, and shippings. For example, the IoT platform for manufacturing provide solutions in identifying the need for an equipment repair before the machinery breaks down, thus minimizing the equipment availability loss in the production lines. In healthcare, IoT wearables monitor the conditions of patients and notify the doctors when the conditions of patients change.
Big Data Use Cases: Big Data analytics is evolving in business areas like finance, marketing, health service and retail business. For example, in e-commerce it use to analyze the interactions between consumers and sellers, as well as to predict their preferences to make purchases as individual as possible. In healthcare, Big Data can use to find new drugs or to prescribe patients with specific diseases the right treatment due to a huge number of patients’ data.
The Relation between IoT and Big Data
Although IoT and Big Data are different, they cannot function independently of each other. The IoT devices create data that the Big Data platforms use to provide deeper analysis of the raw data . For instance, data gathered from different Industrial Internet of Things IoT devices measuring industrial equipment is analyze by big data systems to look for signs of inefficiency or impending equipment failure. The IoT in parallel with Big Data provides real-time information that can couple with powerful analytical tools to provide better business decisions.
Conclusion: Understanding on How IoT Is Connected With Big Data
IoT and Big Data might be different in terms of their objectives and applications, but without one the other wouldn’t be nearly as effective in supporting the functionality of contemporary digital technologies. Secondly, it identifies IoT devices as a never-ending stream of real-time data to feed Big Data systems as raw material. Such synergy makes it possible for various business and industries to establish visibility, optimize operations and evolving decision making mechanisms.
To take advantage of this synergy, therefore, a business must commit to the IoT platform and Big Data. The IoT platform helps gather the data while the Big Data system helps organizations to make sense of the data collected which in turn help organizations to grow, innovate and become efficient. In its combined form, IoT and Big Data are the essential engines for the future smart and data-driven industries.
