IoT are devices that can connect and exchange data with other devices and networks through the internet.
Meanwhile, Big Data is a method of assembling, analyzing, and organizing the massive amount of data collected through the IoT device into understandable datasets that inform companies on how to optimize their processes, which can be beneficial for improving business.
In this article, we are going to talk about what is big data analytics in IoT and how is IoT related to Big Data Analytics.
What is the IoT?
An IoT can be described as a device or object that is connected to the Internet. These devices are embedded with software, sensors, processing ability, and various other technologies through which the device can associate and exchange information or data with other devices through the Internet or other communication networks.
Some of the examples of IoT devices are gadgets, sensors, actuators, machines, and much more through which you can transmit data to other networks or devices using the internet.
How does IoT use big data?
As we know, IoT devices help connect and exchange data from numerous devices and systems over the Internet, Big Data analytics helps make the data collected by IoT devices more understandable.
IoT devices collect a wide range of unstructured data, Big data helps organize, analyze the data, and further organize it into smaller data to provide a clear and easy-to-understand insight into how their processes are working, this is how IoT influence big data.
The difference between iot and big data is that IoT Devices connect and exchange data, but Big Data helps analyze, organize and manage that data. Big Data analytics can generate numerous types of insights when it’s used with IoT which can help guide and improve the decision-making process.
There are different types of insights provided by Big Data when used with IoT such as descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics.
- Descriptive analytics: It works towards providing insights into the real-time performance of the connected device. It can be utilized for providing a clear understanding of how the device has been used by customers, identifying anomalies, and it can even be used for locating a connected device.
- Diagnostic analytics: It works towards answering all the “why” questions of the organization behind the descriptive analytics. It can be used to provide a clear understanding of why the device is running a particular way or why certain outputs have been produced and much more.
- Predictive analytics: Just like the name suggests, is utilized for producing probabilities or predictions on how the device will function in the future. This type of analytics function by using machine learning technology and help analyze past data to provide these insights. These types of analytics are especially beneficial for the servicing of IoT devices as they help organizations anticipate any potential failure or services of the device beforehand.
- Prescriptive analytics: It helps answer the question, “What should we do?.” It utilizes advanced processors and tools to identify the data recommended through predictive analytics and create a strategy for moving forward.
IoT big data characteristics
There are a total of six characteristics of big data in iot which include specific features and capabilities, which are mentioned below:
Volume refers to the high amount of information and data gathered by IoT devices every second. This includes various data collected through customers’ social media, cars, cell phones, credit cards, M2M sensors, and much more.
Value is one of the most important “V” when it comes to marketing and business. Since it’s not only about the massive amount of information that gets collected, instead it’s more about how much valuable data is stored. The value of big data comes from pattern recognition and insight discovery which can be beneficial for better customer relationships, effective operations, and other quantifiable business benefits.
Veracity refers to the “reliability” or “accuracy” of the data and information generated. Since the gathered data by IoT devices contains structured and unstructured data it’s important for Big Data to look for an alternate method to filler them or organize them in a form that can specifically state the data is crucial in business developments.
Velocity is the “Speed” at which the companies receive, store, and manage their data. It’s essential to generate data on demand at a quick speed. For example, the total number of search queries received within a day, the number of social media posts, and more.
Lastly, we have variety which refers to the diversity and range of different data types. As we know IoT devices gather an extremely high amount of data which includes unstructured data, semi-structured data, and raw data which can easily be managed and organized by Big Data.
Numerous manufacturers are working towards developing IoT devices that similarly capture, manage, and analyze data on multiple IoT devices. For example, change in the meaning of phrases and keywords in text analytics.
What is IoT Big data used for?
IoT in Big Data is used for extracting and analyzing a wide range of unstructured data. Big data helps organize and analyze the data collected through social media, cars, cell phones, credit cards, M2M sensors, and more.
It further organizes the extensive data collected into smaller data to provide a clear and easy-to-understand insight into how their processes are working. This helps provide better business insights to companies which can help them in making better decisions and improving customer experience.
Big Data IoT Applications
Nowadays the majority of organizations are accessing the benefits of Big Data a lot to help grow their business. Here are some of the applications that are utilizing the benefits of Big Data Iot effortlessly.
1. Education Industry
The Education Industry is filled with extensive amounts of data and information related to courses, students, faculties, and much more. Big Data can help analyze these data and provide insights that can be beneficial in improving the operational effectiveness and working of educational institutes.
The Big Data lot can help customize programs and schemes using students’ learning history, analyze student’s data and provide career prediction, reframe course material, and much more.
2. Healthcare Industry
The Healthcare industry also tends to generate a high amount of data and Big Data lots. The Wearable devices and sensors introduced in the industry can be beneficial in providing real-time feed to the electronic health records of the patient.
It can help analyze and manage these data in the healthcare industry and provide various benefits such as predicting outbreaks of epidemics, helping avoid preventable diseases by detecting them early, and more. This way patients can also be provided with evidence-based medicine and treatment which has been identified and prescribed by properly researching the previous medical results.
3. Transportation Industry
Big Data has been highly used in the Transportation Industry as it can help make the entire shipping and delivery process more efficient and easy. Big Data can help understand and estimate users’ needs on various routes along with various modes of transportation which can be utilized for route planning which can be beneficial in reducing wait time.
People can also estimate any congestion or traffic patterns such as using Google Maps to locate areas with minimum traffic-prone routes. Real-time processing of Big Data can also be beneficial in looking out for any accident-prone areas beforehand to maintain safety levels.
4. Government Sector
There is no doubt that government sectors of any country collect massive amounts of data almost every day. This includes a variety of records and databases on citizens, energy resources, geographical surveys, and much more. Big Data IoT can help analyze and study this data at a faster pace and help them make essential decisions on various political programs quickly.
Government sectors can also use Big Data IoT to catch tax evaders. Apart from this, it can also be helpful in identifying areas that require immediate attention and staying up-to-date on various tracks such as livestock, existing land, and more.
5. Weather Patterns
Weather sensors and Satellites are deployed worldwide, through which a high amount of data is collected. Further, this data collected contributes to big data and can be used to monitor these weather and environmental conditions. It can help in weather forecasting, studying global warming, understanding the patterns of natural disasters, and much more.
Real-Life Examples of Big IoT Data
To understand how Big Iot Data can be beneficial in the real-life world, here are a few examples of the companies and businesses that have invested in Big IoT data:
UPS is one the largest shipping companies in the world that provides door-to-door services through its reliable and affordable shipping. UPS has been involved in using Big Data analytics and Sensor data to improve efficiency, lessen the environmental impact, and at the same time save money.
It utilizes sensors on its delivery vehicles to monitor the speed of the delivery per gallon, mileage, and engine health. UPS also uses big data through ORION. The tool utilizes millions of address data points, and various other data and information collected through the deliveries to ensure the delivery routes are optimized for better efficiency.
Spotify is one of the leading music-providing platforms in the music industry that utilizes Big Data Analytics to collect data from music streams all around the world. By collecting this information it analyzes their data and provides informed music recommendations to its users.
Apart from Spotify, another popular subscription platform, Amazon Prime also utilizes Big Data to analyze the data and provide suggestions to its users.
3. King’s Hawaiian
King’s Hawaiian is a famous food company that utilizes IoT and Big Data to monitor the performance of the factory. It connects machines to their bread production factories through which the employees can easily monitor the overall performance, reduce any sort of downtime of the machine, and lower maintenance costs.
4. John Deere
John Deere is an impressive manufacturing company that has been utilizing Big Data and IoT for monitoring moisture levels. Further, it also sends appropriate data to the farmers through a wireless system. The environment sensors can help measure the air and soil temperature, rainfall, humidity, leaf wetness, and solar radiation which is excellent to discover when crops are reaching their moisture levels.