Data Mining: Techniques, Applications, Security, Privacy, And Ethical Implications

Introduction to Data Mining

Question 1:

The data mining is used in the business mainly for the discovering of the different patterns and the relationship of the data to handle and easily make better decisions for the business. There are certain kind of help with the spot sales trends to handle the development with the smarter marketing campaigns and accurately handling the customer loyalty as well. (Delen et al., 2017). It includes the techniques where there is:

1. The market segmentation to identify how the customers are able to buy the same products from the company.
2. It is easy that the customer churning could be done with predicting about which customer is likely directing towards leaving the company and then going to its competitor.
3. The fraud detection is for identification of different transactions which are going to take place.
4. The direct marketing is to apply and identify all the prospects based on how the mailing list is administered for a better and a higher rate of response.
5. There is a possibility with interactive marketing which predicts about how the individual is able to access the website with the interested factor, likely to be seen in it.
6. The market based analysis is to understand about the products and the services which are for the different products and the purchases that are done, e.g. beer and diapers.
7. The trend analysis is mainly to reveal about how there is a possibility of work on differences when set with the customers this month or the last month. (Rouger et al., 2017).

The data mining works with the automated systems and the setup of the trends and behaviours. It includes the automation process with finding different perspectives that are related to the information stored in the database. The questions are about how there are hands-on analysis which could be used for answering from the data. the example for this is the targeted marketing with the promotional mailings to identify the different returns on the investments. The data mining is through the identification of the hidden patterns as well.

Question 2:

Wang, F., Li, X. L., Wang, J. T., & Ng, S. K. (2017). Guest Editorial: Special Section on Biological Data Mining and Its Applications in Healthcare. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 14(3), 501-502.

The article related to the biological processes and how it is able to improve the healthcare. The data mining techniques are used for the knowledge discovery and then deriving the data which includes the driven insights from the different sources of data. They are important for the biology and healthcare. (Ryoo, 2016). The major focus is on how the researchers able to work on the bioinformatics, healthcare information, data mining to handle and share the research. The Electronic Health Records with determining the healthcare systems is coupled with the linking to EHR for a proper research in the different large-scale precision medicine research.

Question 1:

Security: The data mining is the process which includes the sequence that is for the queries and for extracting the information that comes from the larger amount of the data. through this, there is a growth of development with data mining techniques that cause the security problems. The security needs to be checked with the build-up of certain accuracy models and for the data analysis without any right to make use for the specific customer records. The development of the such models is major concern with large amount of information that could be accessed. The data warehouse works on monitoring of data access with allowing the restricted access to data warehouse for data mining purpose like Walmart. (Marinakos et al., 2016). The company holds the extensive database of the stock, stores where there is a need to mine the data for selling the products.

Privacy: The privacy is considered as an important factor for handling the information about the customers with storing the data in warehouse. For this, the access is based on the information and how to use the data for the data extraction from warehouses. It includes the finding of different information and the relationship about the customers and then making important connections which will help in setting the privacy at risks. The data mining also includes data arrangement so that it is easy to cover customer’s information with necessitating confidentiality and privacy. IBM works on mining methods which allow the individual privacy and creating model data accuracy. (Tasioulas, 2016). The Privacy is preserved with data mining method where the company can easily gather the information with impeding forms on customer right privacy.

Data Mining Techniques and Applications

Ethical implications: The use of the data mining has major ethical implications. It has been seen that the different companies are facing issues about deciding which company should make the person aware of the information to be stored with the proper future data mining. The person also gives the option for opting out for the data collection where the company can also affect the competitive advantage in the market place. The company need to decide about the ethical concern which will lead to the loss in the good will from the consumers. One needs to make use of the data mining techniques that will be for the particular applications along with considering the wisdom. (Witten et al., 2016). The example is the data mining can be for the discrimination of the people which is set in regard to the racial and the sexual orientations. The use of the data mining is the way that is important and found to be illegal. The individuals need to be completely protects with any form of the unethical use about the personal information with the major focus on the ethical themes which relate to the privacy and the individuality. The importance is based on the value with the protection to make sure of the people who are being treated. With this, the people should also discuss about the major significance of the threats and the dangers that are consistent to discuss about the different kinds of the ethical issues. The data mining is neutral with the way that could be used for the questions and the concerns about the ethics. This will help in making the people safe.

Question 2:

For the business sector, the security is important for the company like Walmart who focus on handling the extensive database with the different details about the stores, stocks and the other collected data. (Shmueli et al., 2016). It also includes about how they are able to handle the information which is set in conjugation to the database of Walmart and the sales of the products. The restrictions are based on the accessibility with the products that are being offered related to the security and the privacy concern. The major concern is about how the products are being offered by the companies and how Walmart works on the different concerns of security and privacy as well.

In the company like IBM, there is a need to create and work on accuracy of models. This depends on the randomisation of the personal information of the customer where there is a use of the privacy preserving data with company trying to gather the information and handling the privacy rights as well.(Shumeli et al., 2017).

In the ethical concern, the companies need to focus on how the data is being provided and whether it falls under the unethical issues or not. For this, there is a need to maintain the privacy and confidentiality of the system with better individuality that could easily be valued and protected depending upon how the people are going to treat. With this, the experts also consider the data about how to handle the mining with the neutral way to use and work with different questions and the concerns about ethics.

Here, the potential is based on working over the control and accessing to the information with the physical space to handle the access points. They are found in the big data records to store the information with the check over the size and the distribution that holds the broad range of access as well. The software works on the components where the security is enough for the company to handle the potential attack. The Hadoop is the collection with the software components and to handle the corporate data platform based on large scale adoption process. The consumer demands the security and the privacy where the countermeasures are mainly related to the encryption and then accessing the control and the intrusion detection. (Ryoo, 2016). This will help in handling the information where the authorities and the companies like Apple, Google and Amazon would require providing intelligence with the decrypted data version.

Reference

Delen, D., Eryarsoy, E., & ?eker, ?. (2017, January). Introduction to Data, Text and Web Mining for Business Analytics Minitrack. In Proceedings of the 50th Hawaii International Conference on System Sciences.

Marinakos, G., & Daskalaki, S. (2016). Viability prediction for retail business units using data mining techniques: a practical application in the Greek pharmaceutical sector. International Journal of Computational Economics and Econometrics, 6(1), 1-12.

Roiger, R. J. (2017). Data mining: a tutorial-based primer. CRC Press.

Ryoo, (2016)., Big Data, Human Rights and the Ethics of Scientific Research – Opinion – ABC Religion & Ethics (Australian Broadcasting Corporation). Available at: https://www.abc.net.au/religion/articles/2016/11/30/4584324.htm 

Shmueli, G., & Lichtendahl Jr, K. C. (2017). Data Mining for Business Analytics: Concepts, Techniques, and Applications in R. John Wiley & Sons.

Shmueli, G., Patel, N. R., & Bruce, P. C. (2016). Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner. John Wiley & Sons.

Tasioulas, (2016)., Big data security problems threaten consumers’ privacy. [online] Available at: https://theconversation.com/big-data-security-problems-threaten-consumers-privacy-54798

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