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ITM 102 Study Guide - June 5, Business Wire, Data Cleansing


Department
Information Technology Management
Course Code
ITM 102
Professor
Catherine Middleton

Page:
of 2
Name: Aaina Jaiswal
Student Number: 500508476
question: 4
Text Mining is a way of determining the patterns and relationships that can help
companies make useful decisions. Text mining can help double the sales of the company that
has recently introduced a new product. This is possible in a way because this tool helps the
companies to search for the negative reviews from the customers. This can help the companies
improve and satisfy the needs of these customers. A company must know two key points about
text mining, " First, 80% of data stored within an enterprise is unstructured textual data. Second,
text mining effectively structures your unstructured data. This allows you to put data in a form
that all other business systems can take advantage of". Because 80% of the data is unstructured
for most business enterprises, text mining helps these businesses improve on the organization of
the information that is really important in making decisions. Text mining also helps in
recognizing the frauds and missed financial opportunities. For example, it can detect if there is
someone who is providing the customers with the false information online. This will help
companies connect to these customers better and introduce their products more effectively. This
tool helps companies make sure the products that are being introduced are satisfying the
customer's needs because it can detect for the negative reviews from the customers and the
companies can use this information to understand which products are in demand. This will help
generate the companies' revenues. There are five major steps in the processes of text mining
which are as follows: Document retrieval, Extractions, Cleansing, Mining and Visualization.
Document retrieval helps regain the documents that being lost which may consist of important
information, it may also be used to regain the resources which can help customers stay connected
with the company. Extraction helps identify the parts of speech as well as what type of entity are
they receiving these responses from. It is helpful for some companies who aim on introducing
their product to certain people or certain organizations and extraction helps these companies
figure out the targeting audience for the companies. Some customers do not like their names to
be mispronounced therefore, extraction is a way to help companies with this sort of a problem.
Data cleansing has an impact on each step of text mining process. It is a way to help companies
make decisions based on certain part of the online reviews such as : keywords, abstract phrases,
or full texts or phrases. Data mining process helps with the link analysis which is a way for
companies to the know the frequent occurrence of the same word or some sort. Frequent
occurrence of some sort can lead to text clustering therefore, data mining helps with the
prevention of such events. Lastly, visualization, this is critical step in the process of text mining.
Companies needs to make a good use of the information and use it effectively. Therefore, text
mining has got both benefits and some critical steps to be considered.
Name: Aaina Jaiswal
Student Number: 500508476
question: 4
References
BONASIA, J. (2002, Jun 05). SPSS looks to strike pay dirt with text mining software
sifts through files company sees big demand for text mining as clients search
documents, e-mail. Investor's Business Daily. Retrieved from
http://ezproxy.lib.ryerson.ca/login?url=http://search.proquest.com/docview/1
027126820?accountid=13631
Clarabridge expands management team, adds chief architect role and 3 new
product and R&D leaders in text mining and CEM. (2009, Apr 06). Business
Wire. Retrieved from
http://ezproxy.lib.ryerson.ca/login?url=http://search.proquest.com/docview/4
44172714?accountid=13631
Lee, T., & BradLow, E. (2011). Automated Marketing Research Using Online Customer Reviews.
Journal Of Marketing Research (JMR), 48(5), 881-894. doi:10.1509/jmkr.48.5.881
Laudon, K. C., & Laudon, J. P. (2013). Management information systems: managing
the digital firm (6th Canadian ed.). Toronto: Pearson Canada.