Term Paper on "Data Mining in Business Research Executive Summary"

Term Paper 4 pages (1160 words) Sources: 3 Style: MLA

[EXCERPT] . . . .

Data Mining in Business Research

Executive Summary

The perfect storm is brewing over analytics and their use to define the

future of data mining and its associated techniques and technologies,

(Columbus 1). The use of data mining, its adjunct technologies for text

mining and the ability to interpret, analyze and create linguistic models

from unstructured content is revolutionizing the concept of data mining

away from being purely used for structured content in data warehouses to

now encompass unstructured content found throughout organizations globally.

Text mining's growth is attributable to many factors, which include but

are not limited to the following. First, there is the rapid growth and

popularity of Google, and its search engine technologies and many patents

on taking unstructured text content and turning it into intelligence

(Google, et.al.). Their most famous patents surround latent semantic

indexing, an approach where a model is constructed from the similarities of

linguistic content to create threads of intelligence on specific topics.

There's also the development by some of the world's largest software

companies in the area of Natural Language Processing (IBM Natural Language

Processing, 3) , where unstructured or un-organized content is captured,

analyzed for trends and assumptions of their interrelationships, and then

reported back (CoGenTex, 4). This is a specific technology used for

interpreting the "chatter" of terrorists and the intercepted cell phone, e-

mail, and
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Instant Messaging done between cells in the United States and

other nations. This technology can create in effect a hierarchy of senders

and receivers of content and what their key messages are, which allows

intelligence organizations worldwide to plot the organization charts of

terrorist organizations. Second, text mining is growing rapidly due to the

burgeoning growth of blogs, and the insights obtainable from these and

other forms of consumer-generated media. Companies are actively mining

blogs to discover what consumers are saying about them. Third, text mining

is becoming pervasive as many companies of all types have their most

important information stored in systems as comments, and the need to

interpret these comments and form a common thread of knowledge is needed.

Fifth, compliance in its many forms is making text mining a critical

ingredient of every manufacturer's mix of tools for getting a forward look

at what is happening in their installed base of customers. Warranties

specifically have been a focus on the part of American automobile

manufacturers given the TREAD Act, which is based on the strong of

Firestone Tire accidents on Ford Explorers (Mixer, 1). The Sarbanes-Oxley

Act also is forcing the issue of text mining as well. (Hagerty, 2) Taken

together, all these factors and more are making text mining a critical link

in both government and commercial strategies for defense, security,

insight, and growth.

Data mining's growth has equally been impressive, yet can be attributed to

different factors than text mining. First, there is the demand from within

many companies of creating a centralized repository of all content so the

data mart or data warehouse can quickly accessed for insights and

intelligence (Columbus and Murphy, 4). The future of data mining is in

predictive analytics, which is the ability to interpret then define the

future of key areas of any company, based on their previous performance.

The intent of this paper is to provide insights into these areas of data

mining, and the currently high levels of growth analytics use and

applications software are experiencing as a result.

Using Data Mining in Business Research

The ability to create differentiated and effective… READ MORE

Quoted Instructions for "Data Mining in Business Research Executive Summary" Assignment:

There are three sources for this Module's Case:

Data Mining *****“ Seven Years Later, Lessons Learned: http://www.crm2day.com/library/EpAZpuAFyAzpbJTtYp.php

Mike Chappie's Data mining: An Introduction: http://databases.about.com/od/datamining/a/datamining.htm

Cliff Allen's Mining for Gold: http://retailindustry.about.com/gi/dynamic/offsite.htm?site=http%3A%2F%2Fclickz.com%2Farticle%2Fcz.681.html

When you've read through these sources and through the rest of the readings for this Module,, please compose a short (ca. 4-6 pages) paper on the general topic of data mining in business research. The following questions are suggested as things to think about, not necessarily as point to be answered specifically in your paper:

What do each of these sources tell you about the data mining phenomenon? Why has it become widely used only in recent years?

What do the critics of the procedure say about it?

How does data mining fit into the typology of research that we discussed in earlier Modules?

How believable are the results? Why?

What do you think is the long-term role for data mining in the field of business research? Why?

*****

How to Reference "Data Mining in Business Research Executive Summary" Term Paper in a Bibliography

Data Mining in Business Research Executive Summary.” A1-TermPaper.com, 2007, https://www.a1-termpaper.com/topics/essay/data-mining-business-research/2057. Accessed 27 Sep 2024.

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1. Data Mining in Business Research Executive Summary [Internet]. A1-TermPaper.com. 2007 [cited 27 September 2024]. Available from: https://www.a1-termpaper.com/topics/essay/data-mining-business-research/2057
1. Data Mining in Business Research Executive Summary. A1-TermPaper.com. https://www.a1-termpaper.com/topics/essay/data-mining-business-research/2057. Published 2007. Accessed September 27, 2024.

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