Understanding the relationship between IoT and Big Data - JAXenter

More devices and objects are now linked to the internet, transmitting the data they gather back for the purpose of analysis. Here, the goal is to utilize this data to learn more about trends and patterns that can be utilized to make a positive impact on our lifestyle, energy conservation, transportation, and health. Nevertheless, the data itself doesn't create these objectives, but rather its solutions that emerge from examining it and locating the answers we need.

In relation to this future, two terms that have been discussed are the Internet of Things(IoT) and big data. These are closely intertwined and although they are not the same thing, it is very hard to talk about one without the other. Before we analyze their connection, let us take a much closer look at these two practices.

Big Data

The term big data existed long before IoT arrived to carry out analytics. When the information demonstrates veracity, velocity, variety and volume, then it is interpreted as big data. This equates to a large quantity of data that can be both unstructured and structured, while velocity refers to data processing speed and veracity governs its uncertainty.

Internet of Things

The notion of IoT is to take a broad range of things and convert them into smart objects — anything from cars, watches, fridges and railway tracks. Normally, the products that wouldn't be linked to the internet and able to acquire and manage data, are provided with computer chips and sensors for the purpose of gathering data. Nevertheless, unlike the chips utilized in mobile devices, smartphones and PCs, these chips are utilized mostly for collecting data that specifies product performance and customer usage patterns.

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The data from IoT devices lies in big data and this information is measured against it. Soon, IoT will touch each and every facet of our lives: smart homes, manufacturing, transportation, and consumer goods like wearables, smartphones and more.

Bringing IoT and Big Data together

This disruptive technology needs new infrastructures, including software and hardware applications as well as an OS; enterprises must handle the influx of data that begins flowing in and examine it in real-time as it evolves by the minute.

That is where big data arrives into the picture; big data analytics tools have the capacity to handle large volumes of data generated from IoT devices that create a continuous stream of information.

But, in order to differentiate between them, IoT provides data from which big data analytics can extract information to generate insights required of it.

However, IoT conducts data on a completely different scale, so the analytics solution must accommodate its needs of processing and rapid ingestion followed by a fast and accurate extraction.

There are many solutions available that provide near real-time analytics on large-sized datasets, and necessarily change a full-rack database into a small server that processes up to 100 TB, so small amount of hardware is needed. The analytics database of next-generation leverages GPU technology, thus enabling even more downsizing of the hardware, i.e, 5 TB on a laptop or a big database in the car. This largely helps IoT organizations correlate the evolving number of data sets, which helps them adapt to changing trends and acquire real-time responses, solving the challenge regarding size and compromising on the performance.

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Challenges

It is projected that by 2020, 20.8 billion things will be utilized around the globe, as the IoT continues its expansion; and as a result, we will also witness major safety concerns and cybersecurity issues, as hackers would break into traffic systems, the power grid, and any other system that is linked and contains sensitive data that can shut down entire cities.

Internet security platforms such as Zscaler provide IoT devices protection against unauthorized access of data with a cloud-based solution. You can route the traffic via the platform and implement policies for the devices so that they won't interact with unnecessary servers.

Big data and IoT share 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 are working together

There are many examples of big data and IoT working well together to offer analysis and insight. One such example is represented by shipping organizations. They have been utilizing big data analytics and sensor data to improve efficiency, save money and lower their environmental impact. They utilize sensors on their delivery vehicles in order to monitor engine health, number of stops, mileage, miles per gallon, and speed.

IoT and big data are creating waves in big agriculture. In this area, the field connects systems monitors to the moisture levels and transmits this data to farmers over a wireless connection. This data will enable farmers to find out when crops are reaching the optimum moisture levels.

And the final example that I would like to discuss here is HR management. The applications of IoT and big data concepts in this field enhances productivity and effectiveness. Some of the advantages here are improved selection of talents and job matching with the required personality skills and traits. According to a survey by peoplehr, it is evident that both big data analytics and IoT have a major role to play in HR management. 

Conclusion

The development of a process for converting data into actionable insight is a crucial part of succeeding at big data and IoT. McKinsey states that open-ended strategies that say,"provide us your data and we will provide you with new insights." are not really sufficient. Enterprises must think via the quality of information they are pulling in and accordingly, design their systems in order to optimize this process.

With an increase in the number of connected devices, organizations will have more opportunities to utilize these devices to collect relevant, useful data that can enhance their business processes.   



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