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Course Title:
Information Technology in Logistics
Course Code:
ITL611S
Department:
INFORMATICS
Programme:
Bachelor of Logistics and Supply Chain Management
Semester 1 2022

Assignment 1
Contributors:
John Paolo Links – 219139954
Franklin Fleermuis - 221026290
Kizano Garoeb – 220132011
Koreni Hausiku – 219077185
Lesley Kandombo - 200226819
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Where large amounts of data is collected, stored, analyzed & used by

organizations, to either improve or provide a service it’s bound to bring up ethical

issues, i.e. how the information is obtained, from where and for what purpose. To

that end, this paper seeks to briefly provide insight into the ethical issues and

challenges surrounding Big Data. Secondly, to illustrate what Big Data Analytics are

and the key technologies it uses.

Big Data is all about capturing, storing, priming, analyzing & simulating

information humans & e-devices create & share using computerized technology &

networks (i.e. social media, purchase records, cellphone GPS signals etc.).

Organizations use this information to improve operations, provide personalized

customer service, and to further their profit/revenue margins. However, this does

raise ethical concerns i.e. how, where and for what purpose information is being

collected. To that effect, Big Data can infringe upon the fundamental principles of

Normative Ethics. For e.g. Privacy concerns. With advanced Big Data analytics, it

becomes increasingly impossible not to identify individuals. Even if information is

anonymously collected, should it be combined with another separate database,

previously unidentified individuals could be re-identified if appropriate data-masking

procedures aren’t followed. Secondly, Individual Autonomy. Organizations use

data collected to influence consumer behavior through their search histories, online

transactions and their use of IoT. Lastly, Least Harm and the problem of unintended

consequences. Unauthorized viewing and possible misuse of information by

unauthorized parties’ cascades into breach of confidentiality, possible financial harm,

identity theft and identity fraud as possible consequences. To that end, Big Data has

its purposes, which is to enhance organizational performance, to hold a competitive

advantage in industry and to make more informed business decisions faster. Yet,
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ethically, Big Data requires a deep-dive into those who wield or have control over Big

Data, as data collected can be used to target and manipulate consumers. As

aforementioned, misappropriation of information can have dire consequences on

those whose data it is collected (data owners), through reduced knowable outcomes

and an increase in unintended consequences.

Furthermore, to gain a clearer understanding of what Big Data entails, the next

section will look at Big Data Analytics, the key technologies around it and the trends

that follow. Big Data Analytics examines or uses advanced analytic

techniques/processes against very large, big data sets (this includes structured,

semi-structed and unstructured data) extrapolated from various sources with the

purpose of disseminating information for various uses. To this effect, this helps

organizations utilize their data with the intention of identifying new opportunities,

making better and more efficient business decisions. This in turn also reduces costs

incurred due to storing vast amounts of data, and aids in developing/marketing new

products and services, made possible through a combination of technologies. These

technologies include, but are not limited to, Cloud computing, Data Management,

Data Mining, Data Storage, Machine learning, Predictive Analytics, HADOOP and

Text Mining to name just a few. Taking the earlier mentioned into account, it

becomes clear that Big Data Analytics is the new future. With its ever-changing field,

with innovations in approaches emerging constantly, Big Data Analytics drives,

hastens and helps organizations stay agile, helping organizations work faster and

giving them a competitive edge over those in industry who have yet to adapt to the

new future that is Big Data. The trends observed in this field of Information

Technology are as follows, an increased use of Predictive Analytics, which is used

where large amounts of data are utilized in industry, to reduce risk and improve
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efficiency. The second trend observed is, is the use of Blockchain for improved data

security as it is regarded as tamper-, and hacker-proof. Lastly, Cloud Migration, the

Internet of Things and Artificial Intelligence are all technologies already

implemented by business organizations and even by consumers in their daily lives,

i.e. smart watches, smart cars, smart appliances or businesses adopting to cloud

storage to deploy information faster and easier, saving time and money.

In summary, aside from the ethical concerns raised by the way Big Data obtains

its information, how its disseminated and the slew of problems that may arise. On a

positive note, Big Data is here to stay as it is a major part of life as we know it. Big

Data fuels decision-making processes. Big Data has aided the advances of many

industries namely, in medicine, behavioral analysis, globalization, in addition to also

making Artificial Intelligence feasible e.g. includes self-driving cars, voice assistants,

and taking over tasks normally requiring human intelligence.

REFERENCES:
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http://www.secureworldexpo.com/10-big-data-analytics-privacy-problems
(accessed 06 April 2022)
2. Herschel, R., & Miori, V. M. (2017). Ethics & Big Data [Review of Ethics & Big
Data]. Technology in Society, Volume 49, 31–36. 0160-791X.
https://doi.org/10.1016/j.techsoc.2017.03.003
3. Howe Iii, E. G., & Elenberg, F. (2020). Ethical Challenges Posed by Big
Data. Innovations in clinical neuroscience, 17(10-12), 24–30.
4. Bormida, M.D. (2021), "The Big Data World: Benefits, Threats and Ethical
Challenges", Iphofen, R. and O'Mathúna, D. (Ed.) Ethical Issues in Covert,
Security and Surveillance Research (Advances in Research Ethics and
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2022)
6. Chonko, L (2012) Ethical Theories. The University of Texas Arlington.
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7. Sas.com. 2022. Big Data Analytics: What it is and why it matters. [online]
Available at: https://www.sas.com/en_us/insights/analytics/big-data-
analytics.html#todaysworld [Accessed 6 April 2022].
8. Business 2 Community. 2022. 5 Top Big Data and Analytics Trends For 2022.
[online] Available at: https://www.business2community.com/big-data/5-top-
big-data-and-analytics-trends-for-2022-02448427 [Accessed 7 April 2022].