1. The Internet of Things (IoT) is both the present and the future. In today's world,
everything is becoming increasingly digital. From smartphones to smart homes to
smart cities, everything is becoming digital. IoT uses the internet to develop a
language between electrical gadgets and sensors in order to make our lives easier
(Kumar et al., 2019). IoT has aided in the expansion of economic, industrial,
educational, and healthcare systems. The term "big data" refers to the large
collection of data generated by various sources such as people, machines, or
sensors (Favaretto et al., 2020).
I've witnessed the industries' fast transformation. For example, back in my home
country eight years ago, the extraction equipment was entirely manual. I'm from the
manufacturing industry and have been working full-time since 2013. I began working
in my native nation of India, then completed my master's degree and moved to the
United States. The data generated by such IoT devices are classified as massive
data. Scientists with specialized knowledge were engaged to update such devices.
Because of the link between IoT and big data, chemical engineers like myself have
the opportunity to collaborate with data analysts. We became not just wiser, but also
more collaborative with other functions and groups. We had to manually place the
raw material, manually record the measurements, and manually keep track of the
output weight of the processed raw materials. A year ago, I was given the
opportunity to work with the extraction unit again in the United States. The whole
equipment was automated as a result of IoT and the need to make industries
smarter. Even while I was at home, I could log on and use the machine.
2. After observing the excellent outcomes, my company established a separate
department for IT personnel. These individuals gathered and examined current data.
We were able to personalize our product lines and meet the demands of the
consumer by using data from the user's preferences. IoT and big data have aided
companies in better understanding their customers' needs. As a result, companies
are able to deliver better services and solutions. For example, I used to work in an
industry that made doorbells and refrigerators. They continued to produce traditional
doorbells and refrigerators, but they also launched a new range of smart doorbells
and smart refrigerators.
Previously, I was only a member of the chemical engineer's team, working within the
factory with little or no connection with the outside world. However, I am now a
member of many technical teams that cooperate and create solutions, including
process engineers and data engineers. New duties came with new roles. I believe
that if we do not have a suitable data structure and architecture, we will fail.
Companies' data capacity is growing exponentially as they become more global with
each passing day. We saw that smart doorbells are connected to the internet in the
previous example. We can't keep the data forever, which is why the users only had
access to the last seven days' worth. We shall be lost in mass data in the future if we
do not discover innovative ways to handle the abundance of data. We wouldn't know
which data to use if we didn't know which data to utilize. We'll have trouble
distributing it, and we'll have trouble keeping the data consistent (Zhu et al., 2009, p.
149). In a manufacturing context, my business still prioritizes chemical engineers
above data engineers. Although we have a separate department for IT, there is still a
lot of traditional thinking when it comes to creating anything. I feel that if my company
3. begins to focus on data engineers, they will be able to develop a solution for storing
more data than seven days.
4. References
Favaretto, M., De Clercq, E., Schneble, C. O., & Elger, B. S. (2020). What is your
definition of big data? Researchers’ understanding of the phenomenon of the
decade. PloS one, 15(2),e0228987. https://doi.org/10.1371/journal.pone.0228987
Kumar, S., Tiwari, P., & Zymbler, M. (2019). Internet of things is a revolutionary
approach for future technology enhancement: A review. Journal of Big Data, 6(111).
https://doi.org/10.1186/s40537-019-0268-2
Zhu, Y., Zhong, N., & Xiong, Y. (2009). Data explosion, data nature, and Dataology.
Brain Informatics.BI 2009. Lecture Notes in Computer Science, vol 5819. Springer,
Berlin, Heidelberg., 5819, 147-158. https://doi.org/10.1007/978-3-642-04954-5_25
