MIS

Data Mining is a significant component of knowledge discovery that is applied to assess a great amount of information and acquire concealed and vital knowledge; the outcome is for beneficiary purpose to companies and governments as well as business settings. This process is used in the best manner in a business setting though similarly in other areas like weather forecasting, health, government operations among others (Wang, 2003). Data mining has a number of benefits when applied in varied companies. Apart from these advantages, it similarly has disadvantages like privacy and security that this paper will discuss. This will be in addition to its use in a company, Pfizer, which is a data mining company that uses data on drugs so as to determine their applicability to a certain population setting.

Advantages of Data Mining

Marketing

Data mining is useful in marketing organizations to create models with regard to their past details to determine who will react to the present market like online marketing. It is using the outcome that marketers will use relevant techniques to sell profitable goods to intended clients.

This method has a number of advantages to retail companies just as marketing. In marketing, a store can have relevant production process in a manner that clients can purchase constantly (Han J. et al., 2011). Moreover, it assists the retail companies to issue specific discounts for precise goods which will attract clients.

Finance/Banking

Data mining offers financial centers with data regarding loans and credit. Through creation of a model from historical client’s data, the bank and other centers are able to know the good and bad loans. Moreover, the process assists them to know mischievous credit card holders so as to as to protect the owners.

Manufacturing

Through the application of data mining in processing of data, manufacturers are able to know tools that are erroneous and get to know the best steps to manage the elements. For instance the semi-conductor companies faced with the problem of knowing the conditions of manufacturing settings. Data mining has been used to know the extent of control aspects that bring about creation of golden wafer. The control elements are applied to process wafers with the needed quality.

Governments

Data mining assists the government companies to acquire and assess the data on financial operations to form trends that are able to know money laundering or other suspicious operations.

Disadvantages of data mining

Privacy Matters

The concern on the personal privacy have been great more so when the internet is successful with social networks and e-commerce (Wang, 2003). Due to privacy matters, people fear that their details are being acquired and applied in other ill way. Businesses acquire details regarding their clients in a number of ways for being aware of their purchasing tendency. On the other hand business do not last for long, some may be lost.

Security Matters

Security is a vital aspect in the current business setting. These companies have details on their staff and clients as well as social security digits and payroll among others (Han J. et al., 2011). There is however concern on how these data are kept. There are a number of issues that rise of hackers who get access and acquire data of clients.

Misuse of Data/ inaccurate information

Information that is acquired using data mining for ethical reasons can be handled in a bad manner. This data may be used badly by individuals or companies so as to benefit from susceptible people or victimize others. Moreover, data mining method is not accurate. Hence if wrong data is used in making decisions, it may lead to significant errors at the final outcome.

Company using Data mining

Pfizer is a company that is keen on applying data mining for clinical trials. The company makes use of complex data mining methods so as to elevate the model of new trials, so as to well understand the new application for present drugs and to assist to assess how the drugs can be applied after they have been permitted for use.

Pfizer applies in depth assessment of clinical trial data; it is applied for getting precise tendencies. The information that is acquired is used to create new studies. There are massive amounts of data that is used, it is first analyzed then used for improved design.

It is up to that that data acquired from data mining studies are applied to acquire a sample size when creating a new test. A good example is a company that looks to acquire drug approved in the US to Japan, the company will be involved in a bridging study so as to show that the drug is effective in the Japan setting (Bio-IT World, 2012). The company may use present data so as to form a new study. In the same manner, a company may assess clinical data after a drug is almost done with its patent period. The company may aim to assess the drug to see if it can be used in another population.

Conclusion

Data mining has a number of advantages to businesses, community and government in addition to the people. Conversely, privacy, security and misuse of data are the major issues if not well handled. The company in focus, Pfizer, has shown that it uses data mining to undertake studies on drugs usage. Several other companies use the same data mining technique to meet their daily objectives; banking and engineering among others.

References

Bio-IT World (2012). Pfizer Data Mining Focuses on Clinical Trials. Acquired from:           http://www.bio-itworld.com/newsitems/2006/february/02-23-06-news-pfizer Han J. et al. (2011). Data Mining: Concepts and Techniques: Concepts and Techniques.     Waltham: Elsevier. Wang, J. (2003). Data Mining. Covent Garden: Idea Group Inc (IGI)

Submission method: Microsoft Word document ,, submissions after 7 pm will not be considered for grading. Label both the word file and the subject of the email as Exam 2
Questions type: Subjective questions (short and long answers) that will evaluate your understanding of the material
Chapters covered: Exam 2 will cover chapters 7, 8, 10, 11, 12, 13, and 14. Exams will be active
during the class hours on the date marked on the tentative schedule above.

I will be posting the exam at 6 pm DUE at 7 pm