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BUS5PB Principles of Business Analytics Assignment Sample

Task 1

Read and analyses the following case study to provide answers to the given questions.

Chelsea is a lead consultant in a top-level consulting firm that provides consultant services including how to set up secure corporate networks, designing database management systems, and implementing security hardening strategies. She has provided award winning solutions to several corporate customers in Australia.

In a recent project, Chelsea worked on an enterprise level operations and database management solution for a medium scale retail company. Chelsea has directly communicated with the Chief Technology Officer (CTO) and the IT Manager to understand the existing systems and provide progress updates of the system design. Chelsea determined that the stored data is extremely sensitive which requires extra protection. Sensitive information such as employee salaries, annual performance evaluations, customer information including credit card details are stored in the database. She also uncovered several security vulnerabilities in the existing systems. Drawing on both findings, she proposed an advanced IT security solution, which was also expensive due to several new features. However, citing cost, the client chose a less secure solution. This low level of security means employees and external stakeholders alike may breach security protocols to gain access to sensitive data. It also increases the risk of external threats from online hackers. Chelsea strongly advised that the system should have the highest level of security. She has explained the risks of having low security, but the CTO and IT Manager have been vocal that the selected solution is secure enough and will not lead to any breaches, hacks or leaks.

a) Discuss and review how the decision taken by the CTO and IT Manager impacted the data privacy and ethical considerations specified in the Australia Privacy Act and ACS Code of Professional Conduct and Ethics

b) Should Chelsea agree or refuse to implement the proposed solution? Provide your recommendations and suggestions with appropriate references to handle the conflict.

c) Suppose you are a member of Chelsea’s IT security team. She has asked you to perform a k-anonymity evaluation for the below dataset. The quasi-identifiers are {Sex, Age, Postcode} and the sensitive attribute is Income.

In the context of k-anonymity: Is this data 1-anonymous? Is it 2-anonymous? Is it 3-anonymous? Is it 4- anonymous? Is it 5-anonymous? Is it 6-anonymous? Explain your answer.

Task 2

There is a case study provided and you are required to analyse and provide answers to the questions outlined below.

Josh and Hannah, a married couple in their 40’s, are applying for a business loan to help them realise their long-held dream of owning and operating their own fashion boutique. Hannah is a highly promising graduate of a prestigious fashion school, and Josh is an accomplished accountant. They share a strong entrepreneurial desire to be ‘their own bosses’ and to bring something new and wonderful to their local fashion scene. The outside consultants have reviewed their business plan and assured them that they have a very promising and creative fashion concept and the skills needed to implement it successfully. The consultants tell them they should have no problem getting a loan to get the business off the ground.

For evaluating loan applications, Josh and Hannah’s local bank loan officer relies on an off-the-shelf software package that synthesizes a wide range of data profiles purchased from hundreds of private data brokers. As a result, it has access to information about Josh and Hannah’s lives that goes well beyond what they were asked to disclose on their loan application. Some of this information is clearly relevant to the application, such as their on-time bill payment history. But a lot of the data used by the system’s algorithms is of the kind that no human loan officers would normally think to look at, or have access to —including inferences from their drugstore purchases about their likely medical histories, information from online genetic registries about health risk factors in their extended families, data about the books they read and the movies they watch, and inferences about their racial background. Much of the information is accurate, but some of it is not.

A few days after they apply, Josh and Hannah get a call from the loan officer saying their loan was not approved. When they ask why, they are told simply that the loan system rated them as ‘moderate-to-high risk.’ When they ask for more information, the loan officer says he does not have any, and that the software company that built their loan system will not reveal any specifics about the proprietary algorithm or the data sources it draws from, or whether that data was even validated. In fact, they are told, not even the developers of the system know how the data led it to reach any particular result; all they can say is that statistically speaking, the system is ‘generally’ reliable. Josh and Hannah ask if they can appeal the decision, but they are told that there is no means of appeal, since the system will simply process their application again using the same algorithm and data, and will reach the same result.

Provide answers to the following questions based on what we have studied in the lectures. You may also need to conduct research on literature to explain and support your points.

a) What sort of ethically significant benefits could come from banks using a big-data driven system to evaluate loan applications?

b) What ethically significant harms might Josh and Hannah have suffered as a result of their loan denial? Discuss at least three possible ethically significant harms that you think are most important to their significant life interests.

c) Beyond the impacts on Josh and Hannah’s lives, what broader harms to society could result from the widespread use of this loan evaluation process?

d) Describe three measures or best practices that you think are most important and/or effective to lessen or prevent those harms. Provide justification of your choices and the potential challenges of implementing these measures.


1. The case study report should consist of a ‘table of contents’, an ‘introduction’, logically organized sections or topics, a ‘conclusion’ and a ‘list of references’.

2. You may choose a fitting sequence of sections for the body of the report. Two main sections for the two tasks are essential, and the subsections will be based on each of the questions given for each task (label them accordingly).

3. Your answers should be presented in the order given in the assignment specifications.

4. The report should be written in Microsoft Word (font size 11) and submitted as a Word or PDF file.

5. You should use either APA or Harvard reference style and be consistent with the reference style throughout your report.

6. You should also ensure that you have used paraphrasing and in-text citations correctly.

7. Word limit: 2000-2500 words (should not exceed 2500 words).


Task 1


The consideration of the ethical aspect is quite important in ascertaining the implementation of the different research strategies and approaches for attaining goals related to the Australia Privacy Act and ACS Code of Professional Conduct and Ethics. The Australian privacy act implements the protection of the personal data in any given condition. It has been observed that CTO and IT Manager is trying to implement the strategies that relies on the low security of the organization. This low security can be quite fatal to the organization since it is quite prone to be hacked by the cyber-crime experts. The Australian Privacy Act is trying to implement the strategies which can provide the guaranteed security to the information which is available to the organization.

The different types of the strategies are a major contributor to influencing changes in behavior, attitudes, and accuracy and directing them towards improved performance. These can serve as a tool for the organization to develop the strategies that could aid in improving the current scenario regarding the improvement of the data security (Riaz et al. 2020). Data security is a powerful tool for improving the authenticity of the organization and their ability to manage their information over time for best assignment help.

Data security of the Australian government promotes an increased, continuous, and strategic improvement of the existing information about the data. The policy of the government has focused on the upsurge in the implementation of the different types of data of the customers. The data security has the attribute in safeguarding any kind of the vulnerable security to the customers by the implementation of the strategies that could help in augmenting the security of the organizations (Ferdousi, 2020)

In recent years, the modern data encryption strategy is usually implemented for determining the safety requirements of the data which is available to the company for example the salary of the employees and the customer’s details of the organization. This model is commonly referred to as advanced data security. In the event of a stable environment regarding the safe guarded data of the organization this will enable the improvement of the confidence level of the persons towards the organization.

The rise of the utilization of the strategies due to their technological advancements gives them an advantage over the traditional models of data security with the aid of the suitable strategies. It has investigated the impact of the data security technique of the government would improve the current scenario of the data security and would help to improve the current scenario. The information regarding the different modes of the data security strategy has to be considered for relevant fields of any project of the organization (Zulifqar, Anayat, and Kharal, 2021).

Various factors with varying degrees of influence were identified that mediate the implementation of the advanced data security technique. The tools to envisage the impact of the implementation of the data security techniques and the current performance deliverables through the adoption of the innovative data security strategy are all considered in this context. In this context, it is essential to identify the suitable strategies that are doctrine by the government.

However, in the current context the company is trying to implement the low security strategies to protect the privacy of the data which is available to the company. In this regard it can be suggested that the company has given more priority in saving the operational cost of the company by retaining the existing mode of low security technique. However, in this case this strategy is in utter contrast to the existing policies of then government. This strategy will have a negative impact in the current scenario and would also encourage the competing agencies to adopt the similar strategies that partly compromise the security of the information which is available to the company. In this context, it must be noted that the company must ensure the safety of the organization and this should be held in high priority over all the existing conditions.


The company is resorting to the techniques which are not conducive to the current scenario when the government is endorsing the high security of the personal information. In the current scenario, according to me Chelsea is correct in her arguments. Chelsea is endorsing the high security for protecting the data of the company and to prevent the breach of the vulnerable data that could hamper the credibility of the company. Hence according to my opinion Chelsea has an edge in this argument. However, the company is correct in its justification that the high security system is quite expensive. It is to be noted that the advanced encryption system is undoubtedly quite expensive and the company is prone to suffer from huge operational cost in the case of implementation of this expensive strategies. In this case it is also to be noted that the company can implement the less expensive strategies that can give moderate security and improve the existing security system of the organization. The k anonymization strategy would be helpful in safeguarding the data of the customers and the employees. In this connection it is essential to de-identify the available dataset and this could further improve the security of the concerned organization. The k anonymization helps in removing the identities of the several categories and after the removal of the identities the appropriate codes are given to the data so that the breaching of the information can be effectively controlled (Sai Kumar et al., 2022)

Hence the conflict that is existing between Chelsea and the management of the company can be resolved by the implementation of the cost effective strategies by the company. However, the proper strategies must be implemented for safeguarding the privacy of the company as this would help in improving the reliability of the organization. The confidence of the customers and the employees can be improved significantly by the incorporation of the suitable de-identification techniques that could protect the vulnerable data of the organization (Madan, and Goswami, 2018). Thus I highly support the opinion of Chelsea keeping in mind the interest of the company. Thus the amalgamation of cost effectiveness and the data security of the organization aids in the improvement of the present condition of the company.


In this case 2 anonymous systems have been followed. This system is involved in the anonymising or hiding the details of the two categories of the members in the company. These two categories are identity and the post code of the employees. The income of the employee is a very sensitive topic and the proper de identification of the data should be done for ensuring that there is no such breach of vulnerable information that can disturb the reputation of the company. Here in this case the ID of the employees has been denoted with the aid of the codes like1, 2, 3, 4, etc. The post code has also been denoted with the aid of the codes like 308 and 318.There must be some distinctions in the codes that have been applied in this respect. However, all the post codes have not been revealed in this context and this denotes that this data has also been de-identified. However, the other categories like the age, gender and the income of the employees has been mentioned in details. Thus the k anonymization strategy has followed the 2 anonymous systems.

Task 2


The big data driven system of loan approval system is a rapid system of loan approval and it helps in envisaging the loan applications quite quickly and on time (Hung, He, and Shen, 2020.) The credit risk assessment is done in a programme driven manner and this enables the system to handle a lot of application in one given point. Thus this type of computerized big-data driven system helps to reduce a lot of manual labor and this also helps to perform the work in a shorter span. Hence both the time and labor of work is reduced in this type of loan approval system that employs the big data system.


In the case of the big data driven rejection of the loan application there are certain hazards that are associated with this type of rejection. In this case Josh and Hannah were denied of the loans due to the evaluation by the big data and this type of rejection was computerized. In this context the ethical issues are as follows

Creation of confusion-In this case of big data driven rejection of loans the loans are rejected or accepted according to the computer programming. The applications which lack the key requirements are usually rejected in this type of loan approval system. On the other hand, in the case of the manual loan approval, the person responsible for evaluating the loan applications had the duty to explain to the applicants the reason of their failure. However in the case of a computerized system there is no such opportunity to get the required clarifications from the system. This causes a great deal of confusion in the minds of the applicants like Josh and Hannah about the reason for their failure. This lack of knowledge also prevents the applicants to reapply for the loan by fulfilling all the required criteria. Thus this creates a lot of doubt and confusion in the minds of the applicants regarding the rejection.

Lack of transparency and Confidence-As discussed earlier the big data driven loan approval system is devoid of the capability to inform about the exact reason for the failure of the loan application. This creates of confusion and thus this depletes the transparency related to the loan approval system of the bank. The applicants are confused regarding the process and often doubt the unbiased nature of the selection process. The lack of knowledge also heavily contributes to the absence of adequate confidence regarding the loan approval system of the bank.

Doubt regarding discrimination-The lack of knowledge about the existing loan approval system contributes to the development of the doubt in the minds of the loan applicants. The loan applicants are not sure about the unbiased nature of the system since the system is not providing bthe adequate justification of their loan rejection. This instills a belief in the minds of the applicants that they might be the victims of various types of discriminations. This discrimination can be due to the social status r their economic status. The applicants often believe that they have been subjected to discriminatory behaviour due to their existing social or economic conditions. This can be a very disturbing issue since the people rely solely on the banking system for getting loans during their crisis period.


The people of the society heavily rely on the banking system to obtain the required loans during their financial crisis. The loan rejection like Josh and Hannah can have a deep rooted impact on the society since this type of loan rejection does not provide the necessary reasons for the rejection of the loan. This creates a lot of confusion and doubts in the minds of the loan applicants. In such case there is depletion in the transparency and unbiased nature of the banking system. The transparency of the banking system is quite necessary in the society and this damage to the transparency of the banking system disrupts the confidence levels of the people. Furthermore, it has been observed that due to the lack of adequate knowledge about the reasons for the loan of denial, the people might think that the bank is exhibiting a discriminatory approach towards them and this can be quite fatal top the brand image of the bank or the organization which is providing loans.


The big data analysis should not be solely implemented for the selection of the loan application. The applications must not be contingent upon the database and the data analytics of the concerned system (Agarwal et al., 2020). This type of system cannot be applied in all categories of the loan application and the methods should be properly checked before the application. According to my opinion the methods that should be implemented to reduce the cases of discontent regarding the rejection of the loan application are as follows

Current Income-The current income of the individuals must be checked beforehand in order to know whether that concerned person would be able to repay the debt on time. The current income of the individual must be given priority since the person would be able to repay the debt on time only when the person has a steady flow of cash.
Occupation-The occupation of the individual is quite crucial in estimating whether the person can repay the debt on time. The occupation must be stable in nature for determining whether the concerned person would be able to pay off the debt and would be eligible for the lo0an application

Repayment History-It is essential to denote the intention of the people to repay the debt on time. It is essential to prioritize the willingness of the people to repay the debt and in this case it becomes quite imperative to consider the repayment history of the individuals. This indicates that the concerned individuals will be able to repay the debts on time by considering the repayment history of the individuals.

Thus according to my opinion, it is essential to consider the above mentioned parameters since this parameter appropriately estimates the ability of the individuals to repay the debts on time. Thus these parameters must be given more importance than the existent big data driven loan approval system.


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