Business Analytics and Privacy

Business Analytics and Privacy

Abstract

Essentially, the concepts of business analytics and data privacy have erupted enormously in the preceding years. Apparently, there is no organization whatsoever that wishes to be trail behind in adopting these two aspects. For this reason, this essay has clearly defined and demonstrated the two elements. Besides, it has elucidated on the manner in which business analytics relates to data privacy articulating the roles of the latter to business analytics. In addition to this, there is a precise illustration of copious implications organizations are likely to face in the occurrence of business analytics utilization. Lastly, are implications that I am inclined to encounter in the execution of my future career.

Introduction

Conspicuously, the aspect of business analytics and data privacy is reasonably imperative for appropriate consideration in any business environment. Regarding the concept of business analytics and data privacy, there is the concept of big data. Markedly, “big data” is utilized in the event of characterizing data sets that happen to be quite enormous, diverse, and speedily-changing (Xu et al., 2014). Apparently, this aspect demands robust database management structures with aptitudes ahead of those viewed in typical standard query language-based systems. With the existence of current Internet-oriented markets, the element of big data occurs from several primary sources as follows:.

1. Large-scale business structures
2. Online communal diagrams
3. Mobile devices
4. Internet of Things (IoT) and
5. Open or unrestricted data

Distinctly, this essay focuses on achieving the following rationales:

1. Defining and describing the aspect of business analytics
2. Defining and describing data privacy
3. Analyzing the role of data privacy in business analytics activities
4. Evaluating at least two data privacy-related implications for contemporary organizations when utilizing business analytics
5. Reflecting upon the potential for data privacy issues

Background

Notably, the component of business analytics happens to be an area that drives realistic, data-driven alterations in a commercial setup. In simpler terms, it is the practical utilization of numerical scrutiny that aims at offering actionable suggestions. Primarily, the analysts assigned to this area precisely target the manner in which they pertain to the insights they obtain from data (Chen et al., 2012). In essence, their sole objective is to depict substantial conclusions involving a business by responding to precise queries concerning why certain things took place, the events that will occur, and lastly, what steps ought to be undertaken.

Besides, the element of business analytics merges the spheres of administration, commerce, and computer science. Markedly, the commerce aspect demands equally a high-level of the business indulgence as well as the handy confines that are in existence. Besides, the analytical section demands appropriate data indulgence, statistics, and computer science.

Moving forward, the aspect of data privacy or information privacy happens to be a branch of data security that habitually deals with the appropriate managing of data that is the approval, notice, and authoritarian compulsions. More exclusively, possible data privacy apprehensions often spin in the events of:

1. Whether or the manner in which data is distributed with third-parties
2. The way in which information is lawfully gathered or preserved.
3. Regulatory restrictions

Fundamentally, the two aspects are very significant in the event of conducting business in the modern world. Apparently, multiple and assorted companies are implementing the two facets to identify specific customer markets, assess risks, profiling, and segmentation and also in the event of conducting sentiment analysis.

Role of Data Privacy in Business Analytics

Presently, the majority of businesses and administrative agencies are producing and incessantly gathering enormous amounts of data. Fundamentally, the recent augmented focus on considerable sums of data unquestionably has established prospects and platforms to comprehend the processing of such data over plentiful anecdotal domains (Petrescu & Krishen, 2018). However, the latent of big data business analytics draw closer with an aspect of cost. For this reason, the users’ element of data privacy is habitually at risk.

Remarkably, the element of data privacy over the past years has been considered to be quite vital in the functionality and the execution of business analytics in any particular organization (Humprecht, 2018). Data privacy guarantees conformance to solitude conditions and policies that are inhibited in existing big data business analytics and removal events. In essence, this aspect prompts diverse developers to generate a technique in which their respective applications match the seclusion covenants and also ensure that sensitive information is reserved as secretive in spite of multiple alterations or transformations that may be undertaken in the applications and/or in the confidentiality regulations.

Besides, the aspect of data privacy guarantees the element of trust and prevention of numerous risks.  To be more precise, data privacy in business analytics alleviates copious risks that may relate to the pricey occurrences, reputational damage, dogmatic consequences, and other affiliated hazards.  Apparently, ensuring data privacy happens to be quiet imperative in the event of maintaining individuals’ reliance on business analytics.  In actual fact, any business tends to rely upon the belief of its existing and potential customers, commercial cohorts, dealers, and the employees too.  Conversely, in the event, the element of trust vanishes, that particular organization experiences destructive implications.

Implications for Organizations

Evidently, there have been numerous and assorted privacy-related implications arising from the utilization of business analytics. Primarily, business analytics can be considered to a certain extent to be dominant. Nonetheless, the calculations and decisions that implicate subsequently are not at all times correct.

One of the privacy-related implications an organization is likely to face the element of inaccurate data, which as a consequence, would prompt individuals to be denied services, face false accusations or misdiagnosis or also face inappropriate treatment (Ram et al., 2016). In essence, an organization can utilize data files containing inaccurate data about persons, data models that can happen to be erroneous as they recount to meticulous individuals or merely defective algorithms for business analysis. In the event, the utilization of the above takes place; the risks augment as more data is summed up to the sets of data. Regarding this incident, organizations could generate wrong decisions and prompt inapt and detrimental deeds.

The other implication involves a breach of privacy on particular individuals, leading to instances of discomfiture and even loss of occupations. Take a case whereby business analytics to envisage intimate individual particulars such as the due dates of expectant shoppers. In such instances, consequent marketing actions could result in having one or several members of the family realize that a family member was expecting prior to the expectant individual notifying the rest. In essence, this could implicate an uncomfortable and hurtful family condition.

Implications for My Career

In regards to my future career in accounting, I realize that the aspect of data privacy issues in business analytics could mutually positively and negatively affect it. Apparently, this notion is elucidated by the fact that the majority of the organizations presently are utilizing the aspect entirely in the majority of the operations they undertake. If business analytics is conducted effectively, any organization is likely to experience commendable transformations over time. Consequently, the following are some of the implications I am inclined to experience, and besides, the copious actions that I ought to take as a result:

1. Actually one of the impacts is the loss of crucial clients’ data- Conspicuously, this implication can be articulated to the fact business analytics makes use of customers’ data and for this reason, the business analysts have access to the data
2. Secondly is the loss of employment- Take an instance whereby a client’s information is tampered with or utilized in any unlawful act, this could prompt to employees facing a sack
3. Thirdly is the loss of trust within individual employees or an organization- In the incident there happens to be the aspect of data insecurity, this could prompt me as an employee of a particular organization to lose trust particularly with the workforce or preferably the management department of the organization.

For all purposes and intents of ensuring that I deal with these latent implications, I would take the following two measures:

1. Report the employees I find suspicious to me for evaluation and scrutiny
2. Ensure that I do not distribute the clients’ data to unauthorized personnel

Conclusion

In the modern world, the aspect of business analytics is very imperative for any organizational setup. However, this aspect has to go hand in hand with the other facet of data privacy. Besides, it is also wise and advisable for organizations, employees, and even the customers to have an adequate indulgence in these two aspects. Apparently, individuals have to be sophisticated against believing that the utilization of business analytics makes it inevitable that there is no presence of errors. In essence, all the cohorts ought to realize that business analytics do not guarantee complete accuracy.

References

Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS quarterly, 1165-1188. Retrieved from https://www.jstor.org/stable/41703503

Humprecht, H. C. (2014). U.S. Patent Application No. 14/024,628. Retrieved from https://patents.google.com/patent/US20140012833A1/en

Petrescu, M., & Krishen, A. S. (2018). Analyzing the analytics: data privacy concerns. Retrieved from https://link.springer.com/article/10.1057/s41270-018-0034-x

Ram, J., Zhang, C., & Koronios, A. (2016). The implications of Big Data analytics on Business Intelligence: A qualitative study in China. Procedia Computer Science, 87, 221-226. Retrieved from https://www.sciencedirect.com/science/article/pii/S1877050916304914

Xu, L., Jiang, C., Wang, J., Yuan, J., & Ren, Y. (2014). Information security in big data: privacy and data mining. Ieee Access, 2, 1149-1176. Retrieved from https://ieeexplore.ieee.org/abstract/document/6919256/