With each passing day, there is an exponential increase in the number of devices and machines that are getting connected to the internet to transmit information for analysis. Data analysis is done to discover trends that help businesses and organizations forecast future outcomes and be ready for upcoming challenges.
When it comes to data and its analysis, the Internet of Things (IoT) and Big Data are the most talked-about technologies these days.
In this article, we would be discussing how IoT with Big data has revolutionized our lifestyle, How IoT devices work, How does Big Data work, the Relation between IoT and Big Data, the Purpose of Big Data, What most of companies are doing with Big Data, How does it affect us and much more.
So stay tuned with us to know how internet-connected devices and machines have made our lives smarter and faster.
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The Internet of Things is a device that has the ability to transfer data over a network with the least human intervention. IoT devices can be categorized into three parts.
There are devices that have sensors embedded in them and are used as temperature sensors, motion sensors, air quality sensors, soil moisture sensors, etc. These sensors, along with a connection help us to automatically gather data from the environment they are in.
For eg, with the help of soil moisture sensors, farmers get ideas about when their crops need to be watered. These devices have helped people to make better and smart decisions to get favorable outcomes.
You must have seen machines and devices that get data and then act according to that. For Eg, a printer receives a document and then prints it. Another, is when the car receives signals from car keys, it opens the door. There are endless examples of this.
After seeing these two categories of devices, let us proceed to the next category of devices that can receive data, process it, and send it over the network. Let us understand it through an example. Consider a soil moisture sensor that finds out soil moisture and then that data is transferred to the irrigation system through an internet connection.
The data about soil moisture, how many crops are watered, and how well crops actually grow can be gathered and sent to supercomputers that will give the best output after running amazing algorithms.
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No doubt, the Internet has changed the way we used to work and communicate. But the introduction of the Internet of Things, in short, "IoT" has taken this to another level by connecting multiple devices simultaneously to the internet and thus facilitating the interaction between machine to machine and machine to a human being.
An IoT system consists of four fundamental components - sensors/devices, data processing, connectivity, and a user interface. Sensors that are embedded in the device collect the data and transfer it to the cloud through internet connectivity.
After that, the software processes the data and performs actions such as sending an alert, automatically adjusting the devices, etc. At last, we can make any adjustments or needed actions if we want through the user interface.
Big Data is a term that refers to a massive collection of both structured as well as unstructured data that is very difficult to process with traditional techniques. But it is important to analyze business data to get useful insights that help to take strategic business steps.
There are many tools that are used by data analysts to produce useful information from unorganized data.
We are living in a world where billions of Gigabytes of data are generated on an everyday basis. Big Data is analyzed by companies to find out the patterns and trends so that they can offer services accordingly.
Every time we use any technology such as a shopping app, a fitness app, or any smart device, we generate a lot of data that helps companies to track our habits and likings. This helps companies to better understand the needs of the customer and thus produce/offer user-friendly products/services. Big data is not only shaping our lives but also making them better.
IoT and Big Data share a symbiotic relationship and to understand that connection, we need to know the steps involved in the overall workflow.
1. Companies install sensor-embedded devices to collect and transmit data.
2. A huge amount of data (also called Big Data) is collected in a repository in the form of both structured as well as unstructured.
3. Reports, charts, and other forms of data insights are generated using AI-driven analytics.
4. User devices are used to provide further metrics via settings, scheduling, metadata, and various tangible transmissions.
Big data storage is both the repository and source of data. Adding more and more IoT devices can make AI models complex and collect heavier volumes of big data. The ability to process and perform an action on big data depends on the capacity of hardware that helps to pull out necessary and useful data insights.
That is why it is important to invest in efficient hardware and optimized infrastructure design.
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Different techniques are used to collect and store data. One of the major sources to collect data is IoT devices. These devices have in-built sensors that collect data from the environment they are in. The collected valuable data is transferred to the cloud through the internet.
These piles of data are referred to as big data where artificial intelligence and machine learning are used to generate useful insights.
Companies make use of IoT devices to collect data. Since the data stored by IoT devices are in unstructured form, Big Data processes this collected data on a real-time basis and also stores them using several storage technologies. Therefore, the need to get big data in IoT is compelling.
A Group of unstructured data is generated by IoT devices and stored in the big data system.
A big data system is a shared distributed database where a huge amount of data is stored.
Stored data is analyzed using analytic tools like Hadoop MapReduce or Spark
Then, Generate the reports of analyzed data.
IoT and Big Data carry an inter-dependency relationship and hugely impact each other. As IoT grows, it gives rise to the demand for big data capabilities. An increase in the amount of data every day requires more advanced and innovative storage solutions resulting in updating an organization’s big data storage infrastructure.
Big data and IoT have a closely knitted future. It is evident that the two fields will generate new solutions and opportunities that will have a long-lasting impact.
IoT and Big Data help companies in different sectors to make efficient and well-informed decisions and thus offer better services/products. IoT with Big data helps companies to
Examine data
Reveal data trends
Find unseen data patterns
Find hidden data correlations
Reveal new information
IoT in Big Data analytics helps businesses to extract information to get better business insights. Better business insights help in taking better decisions that result in high ROI. Due to an increase in demand for data storage, companies are switching to big data cloud storage which lowers the implementation cost.
The features of Big Data in IoT are reshaping the upcoming generation of the e-health care system and developing an innovative solution in the healthcare field. Big data will now lead to data-driven research instead of hypothesis-driven research. IoT will control and analyze the connection between sensors and existing big data.
In manufacturing companies, due to improper working of equipment and machines, they may end up producing fewer products as they used to do earlier. Installing IoT sensors in the equipment can collect operation data on the machine.
This data will help to find out which equipment is working properly and which requires repair. Hence, a business will never fall short of products.
Installing IoT sensors in vehicles provide data regarding fuel efficiency, tracking the location of the vehicle, delivery routes, and other information that helps in improving organizational productivity.
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With the help of IoT, we can collect big data from weather and satellites to know about the amount of wind and sunlight we can expect within a particular time period. Due to these predictive analytics and machine learning advances, we are capable of predicting weather conditions and taking actions according to that to meet the demand.
For grid operators, intelligent sensors constantly check the temperature of underground cables which helps in taking immediate countermeasures if the cable temperature rises up.
Big data is used to generate findings of power grid components such as input-output curves of transformers that help companies to take action at the right time and prevent load intervention in the power grid.
In this section, we will discuss in-depth how these distinct components help in the functioning of the IoT system.
Sensors/Devices
The sensors or devices collect the data from the environment they are present in. For eg, reading the temperature, analyzing location, etc.
Connectivity
After collecting the data, we need to transfer it for processing, so how to transfer it? The sensor/device can be connected to the cloud through various methods - satellite, WiFi, Bluetooth, direct connection to the internet or ethernet, etc. We can choose any of these methods to transfer the data to the cloud.
Data Processing
Once the data is loaded on the cloud, the software processes it to get the required insights. If the data is favorable or it is as per expectation then nothing to worry about. But what if not? Here is, when the user interface comes.
User Interface
After looking at the data insights, a user can react if it is not going as expected. For eg, if you are monitoring the room temperature from a far location and it is too high as per requirement, then you can maintain it through some apps or trigger some warnings in the home.
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Big data is too complex and large which requires a set of tools and techniques to get useful insights from it. In the market, there are a number of big data tools available that help in storing and processing large data. Here is the list of the top 10 big data tools
Apache Spark
MongoDB
Flink
Kafka
Tableau
Apache Cassandra
RapidMiner
R Programming
Structured, Semi-Structured, and Unstructured. You can mine data from all these data forms using different tools. So, let us know about these forms in depth.
It is a fixed format that is mostly handled by machines, not humans. This type of data contains information that an organization is already using and is stored in SQL databases and data warehouses.
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It is a set of data that does not belong to any data model and cannot be used by computer programs. For eg., Unstructured data files may contain email messages, videos, photos, word-processing documents, audio files, etc.
It is a set of data that does not follow any data model but has some organizational properties and which is why it can be analyzed easily. JSON and XML are types of semi-structured data
Big Data and IoT are playing an important role in technological advancement and transforming our life into faster and smarter. IoT can connect anything that generates data to the internet such as wearable devices, video games, cars, appliances, aircraft, etc to collect data.
Companies can take advantage of Big Data to better understand the preferences and behaviors of the clients and thus improve business performance saving both time and money.
Hope you liked reading this article and found it informative. If you have any doubts, leave a message in the comment section.
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Sainath is a content contributor at MindMajix, a global online training platform. He is specialized in content writing and contribution focus on technologies like Power BI, Tableau, DevOps, Blockchain, Oracle, MS Project, and MongoDB. You can connect with him on Linkedin.