Answer to Question No 1

Figure: Flowchart of Emporium Trading Company 

The modern firms aim to create a compact and healthy concentration towards their customers and therefore undertake data analysing and data mining techniques that are implemented by organizations coming from various sectors of the industry. It is seen that in the utilization of the data by the firms, it is seen that there exists various risks that can have an impact on the operations of the company (Bryman & Bell 2015). The method of sensitivity analysis is even implemented by the organizations in order to aid the consumers to gain knowledge and handle their own ambience for the intention of raising the security, effectiveness and productivity.

The process of data analysis refers to the construction of end results for the data that have been collected by proper scrutiny of the information set. The process is undertaken by taking support of the software and innovative mechanism. The modern companies exploit such mechanism of data analytics in order to discover the accurate information that can lead to rise in profit, increase in the business operations, increase promotional activities and accuracy in their business systems (Kitchin 2013). The data analytic system boots the functions of a firm and thereby leading to rise in competitive advantage and market share over their rivals. The use of these techniques helps to understand the needs of the consumers and the activities of the business.  

Data mining is one of the various tools of data analytics that are mostly used by the organizations in order to gain the accurate results by making use of the data that is most appropriate for a specific organization (Vaismoradi et al., 2013). The best feature of data mining has been its ability to discover the data that are lost in the large data pool that were revealed in earlier researches.

The discovered data are utilized efficiently and thereby giving out the appropriate results. The process of data mining aids the firms to gain knowledge about the ecological situation and the transforming demand and taste of the customers. It is seen that the firms nowadays operate in the international market and thus it is vital for the companies to undertake quick decisions and changes in their policies (Crawford et al., 2014). The management of the firm undertake decisions by looking at the results that have been obtained through data mining. Therefore, it can be said that data mining helps in the increase in the business intelligence thereby giving out the best decisions for the firm. He use of these decisions leads to better mobility of sales, strong and effective quality of data that would lead to rise in the revenue of the organizations.

Answer to Question No 2

The management gains proper information for making proper decisions for the short run. The use of various data analytic equipments helps the companies in gaining information about the purchasing trends of the customer, chances for expansion and increase in market share. The use of data mining is useful for the construction of the report that involves the use of functions of the analysis of the data and helps the researchers in communicating the data contained in the document in a fundamental way (Witten et al., 2016). Data mining is therefore useful for gaining added information regarding the pattern of the companies and the consumers. Therefore, it is pertinent for the firms to gain knowledge about the importance data analytics that are related to the process of making decisions by concentrating on the establishment of opportunities for the firms (Bazeley 2013).

Data mining is the process of undertaking various aspects for the evaluations of the data so that the firms can have an idea about the strategies that are vital with respect to the market condition that can decrease their operational cost and raise their profit. The data are classified into various segments so that each aspect of the data can be utilized for the preparation and recognition of the relationships (Matthews & Ross 2014). Data mining absorbs data from the large pool of datasets that are available globally and thereby enhance their evaluation process to bring out the best results. Data mining is even helpful for the creation of a relationship among the external and the internal factors that comprise in an organization, which takes firm ahead of their competitors. The influence of profits, customer satisfaction and sales are due to the use of data mining (Tinati et al., 2014). Therefore, it can be said that data mining has an important role to play in order to make the decision making of an organization very effective.

The ethical implication of a firm is very much important for the preparation and the maintenance of the consumer database. Ethical implications are relevant for the investigating the data base for the with respect to three aspects that falls under the accountabilities that are divided among the firm and the consumers (Richards 2014). It is known that the firms that are operating in the market have an ultimate aim of securing and protecting the information that are available in their database about the customers. The information that are given out by the consumers consist of their private information as well and the consumers do not want the information they have shared to be leaked outside the company and to be exploited for any unethical activities (Hartas 2015). The customers make use of online services now days and therefore they require sharing their information online to the consumers. The consumers have knowledge that their information are stored by the companies. In order to restrict their personal information from being leaked, it is seen that certain consumers share false information to the companies. The distribution of false information leads to inaccurate results by the firm that leads to inappropriate decision making (Marshall & Rossman 2014).

Data Analysis

Therefore, it is important for the organizations to comply with the code of ethics. The code of ethics is prepared according to the society and the culture where the firm functions. Therefore, culture plays a vital role for the construction of ethics and the ethical standards. The use of ethics is seen in an organization when the employees of the firm are bound ethically that they will not disclose the customer information to anyone or even to other consumers (Leary 2016). This restricts the information from being disclosed and constraints the inappropriate people from misusing the personal information. The information that are available to the companies can be utilized only by the researchers who are undertaking the research and therefore the database remains closed and only a handful of people can access it.

This strategy of implementation of the ethics creates a conscience among the customer and therefore they become satisfied with the role of the organizations. The use of ethics creates a good relationship among the companies and the customers and thereby leading good understanding and bonding (Smith 2015). The consumers when are assured that their information is safe are driven to share their true information that in turn helps the firms to gain the accurate information that can be useful for the construction of the true results that can be useful for the determination of market trend and environment situation that can help in the construction of effective decision making (Pardo & Siemens 2014). There are chances that the information can be leaked with the introduction of new and innovative technologies with time and therefore the companies requires to change their privacy policies from time to time to stay ahead of the fraudulent parties and maintain a just relation between the consumers and the firms (Lyon 2014).   

Conclusion

The analysis of this report reveals that data analysis is one of the significant methods that are used by the organizations in order to gain relevant data that can be used to gain knowledge about the market, environmental situation and the requirements of the consumers. Data mining on the other hand is a type of data analysis tool that is exploited by the firm in order to gain the hidden data that remained unutilized for several years. The information that is gained by through this tool is segregated and the accurate data is taken into consideration.

The second section of the paper deals with the ethical implication of the organizations for the purpose of storing, gathering and the use of the information for the customers. The role of ethics and how the implementation of the ethical codes can create a better relationship among the customers and the organizations are even discussed. This results in the creation of accurate results for effective decision making for the organizations.

Reference List

Bazeley, P. (2013). Qualitative data analysis: Practical strategies. Sage.

Bryman, A., & Bell, E. (2015). Business research methods. Oxford University Press, USA.

Cohen, J. (2016). Methodological issues and strategies in clinical research. American Psychological Association.

Crawford, K., Gray, M. L., & Miltner, K. (2014). Big Data| critiquing Big Data: Politics, ethics, epistemology| special section introduction. International Journal of Communication, 8, 10.

Hartas, D. (Ed.). (2015). Educational research and inquiry: Qualitative and quantitative approaches. Bloomsbury Publishing.

Kitchin, R. (2013). Big data and human geography: Opportunities, challenges and risks. Dialogues in human geography, 3(3), 262-267.

Leary, M. R. (2016). Introduction to behavioral research methods. Pearson.

Lyon, D. (2014). Surveillance, Snowden, and big data: Capacities, consequences, critique. Big Data & Society, 1(2), 2053951714541861.

Marshall, C., & Rossman, G. B. (2014). Designing qualitative research. Sage publications.

Matthews, B., & Ross, L. (2014). Research methods. Pearson Higher Ed.

Pardo, A., & Siemens, G. (2014). Ethical and privacy principles for learning analytics. British Journal of Educational Technology, 45(3), 438-450.

Richards, L. (2014). Handling qualitative data: A practical guide. Sage.

Smith, J. A. (Ed.). (2015). Qualitative psychology: A practical guide to research methods. Sage.

Tinati, R., Halford, S., Carr, L., & Pope, C. (2014). Big data: methodological challenges and approaches for sociological analysis. Sociology, 0038038513511561.

Vaismoradi, M., Turunen, H., & Bondas, T. (2013). Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study. Nursing & health sciences, 15(3), 398-405.

Witten, I. H., Frank, E., Hall, M. A., & Pal, C. J. (2016). Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann.