It Essay - Data Mining
The Other Side of Data Mining
Maral Aghazi – 500287851
November 10th,2012
ITM 200
Professor Roger De Peiza
"As we and our students write messages, post on walls, send tweets, upload photos, share videos, and “like” various items online, we’re leaving identity trails composed of millions of bits of disparate data that corporations, in the name of targeted advertising and personalization, are using to track our every move” (McKee, 2011). Data mining has become extremely prevalent in today’s society given the vast advancements in technology, particularly the internet. Companies as well as the government are able to discover mass amounts of information about people, which those people are unaware of themselves. This allows companies to research and cater to its consumers in quick and efficient ways, by sifting through large amounts of data and compiling the information necessary for their success. In terms of meeting customers’ needs by evaluating trends and group behaviours it is beneficial to society, however there are also detrimental consequences given the sum of personal content available on many social networking platforms. This paper will define data mining, the impact it has grown to have and it’s further development in the future.
Data mining is a concept with which most of us may not be familiar in terms of its prevalence and importance. Data mining is defined as an “analysis of large pools of data to find patterns and rules that can be used to guide decision making and predict future behaviour” (Laudon, Laudon & Brabston, 2011). This can be used to discover trends for essentially everything. While purchasing our daily cup of Starbucks coffee in the morning may seem meaningless and irrelevant to us, we could very well be part of a compilation of data used for further research. There are many ways in which information can be obtained via data mining. The first of these methods is association. Association refers to the relation between the
Maral Aghazi – 500287851
November 10th,2012
ITM 200
Professor Roger De Peiza
"As we and our students write messages, post on walls, send tweets, upload photos, share videos, and “like” various items online, we’re leaving identity trails composed of millions of bits of disparate data that corporations, in the name of targeted advertising and personalization, are using to track our every move” (McKee, 2011). Data mining has become extremely prevalent in today’s society given the vast advancements in technology, particularly the internet. Companies as well as the government are able to discover mass amounts of information about people, which those people are unaware of themselves. This allows companies to research and cater to its consumers in quick and efficient ways, by sifting through large amounts of data and compiling the information necessary for their success. In terms of meeting customers’ needs by evaluating trends and group behaviours it is beneficial to society, however there are also detrimental consequences given the sum of personal content available on many social networking platforms. This paper will define data mining, the impact it has grown to have and it’s further development in the future.
Data mining is a concept with which most of us may not be familiar in terms of its prevalence and importance. Data mining is defined as an “analysis of large pools of data to find patterns and rules that can be used to guide decision making and predict future behaviour” (Laudon, Laudon & Brabston, 2011). This can be used to discover trends for essentially everything. While purchasing our daily cup of Starbucks coffee in the morning may seem meaningless and irrelevant to us, we could very well be part of a compilation of data used for further research. There are many ways in which information can be obtained via data mining. The first of these methods is association. Association refers to the relation between the
References: Alexander, D. (n.d.). Data Mining. Instructional Technology Services. Retrieved November 2, 2012, from http://www.laits.utexas.edu/~anorman/BUS.FOR/course.mat/Alex/#9 CTVNews. (2012, March 18). London, Ont. police turn to social media to find rioters. CTVNews. Retrieved November 1, 2012, from www.ctvnews.ca/london-ont-police-turn-to-social-media-to-find-rioters-1.783735 Data mining spurs innovation, threatens privacy (2009). Washington, D.C., United States, Washington, D.C.: National Public Radio. Retrieved from http://ezproxy.lib.ryerson.ca/login?url=http://search.proquest.com/docview/190846049?accountid=13631 Dharminder, K. (2011). Rise of Data Mining: Current and Future Application Areas. International Journal of Computer Science Issues, 8(5), 256-260. Retrieved November 7, 2012, from http://www.ijcsi.org/papers/IJCSI-8-5-1-256-260.pdf He, J. (2009). Advances in Data Mining: History and Future. Third International Symposium on Intelligent . Retrieved November 1, 2012, from http://ieeexplore.ieee.org.ezproxy.lib.ryerson.ca/stamp/stamp.jsp?tp=&arnumber=5370232&tag=1 Laudon, K. C., Laudon, J. P., & Brabston, M. E. (2011). Management information systems: managing the digital firm (5th Canadian ed.). Toronto: Pearson Prentice Hall. McKee, H. (2011, December 11). Policy Matters Now and in the Future: Net Neutrality, Corporate Data Mining, and Government Surveillance. Computers and Composition. Retrieved November 1, 2012, from journals.ohiolink.edu/ejc/search.cgi?q=authorExact:%22McKee%2C%20H.A.%22&sort=date McMillan, G. (2011, September 11). Twitter Reveals Active User Number, How Many Actually Say Something | TIME.com. Tech | News and reviews from the world of gadgets, gear, apps and the web | TIME.com. Retrieved November 1, 2012, from http://techland.time.com/2011/09/09/twitter-reveals-active-user-number-how-many-actually-say-something/ Vaidya, J., Zhu, M., & Clifton, C. W. (2006). Privacy preserving data mining. New York: Springer. What is data mining? (1998). Industrial Distribution, 87(3), 49-49. Retrieved from http://ezproxy.lib.ryerson.ca/login?url=http://search.proquest.com/docview/204966526?accountid=13631