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How Data Mining Can Help a Business

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How Data Mining can help a business Data mining can help business strike gold when preparing products for a consumer. However, what is data mining? The University of California, Los Angeles (UCLA) defines data mining as “the process of finding correlations or patterns among dozens of fields in large relational databases” (N.D.). Oracle helps refine this definition, as this method “provides a way to get at the information buried in the data” (Oracle, N.D.). Oracle goes on to state how data mining helps find “patterns that sometimes elude traditional statistical approaches to analysis because of the large number of attributes, the complexity of patterns, or the difficulty in performing the analysis” (N.D.). There is petabytes of data for many companies and agencies to sort though. Many turn to cloud systems, or run programs that extract the data for them from their sources. UCLA goes on to define data as including operational data, nonoperational data, and Meta data. They use this information to help find associations, relationships, and/or patterns with in the data. They use this to develop knowledge about historical data. Companies like Volvo started to leverage cloud computing. They felt that each car could provide information that improved each car as it was built and driven. They also felt that the information provided by each car could improve the consumer experience while driving one of their cars. To support this, Volvo developed a sensor suite that contained hundreds of sensors and CPU’s within the car itself. This allowed Volvo to use 1.7 terabytes of data and use the information to ensure that their cars evolved. Even the police force uses data mining to assist in solving crimes or preventing crimes. They use Computer Comparison Statistics, or COMPSAT. Detective Jeff Godown in a report for The Police Chief describes the core processes as a method of reviewing quantifiable statistical indicators, using the locations, types of crime, how many crimes were committed, the time of day of the crimes, and other factors. This allows the program to identify the time of day and locations of where a crime is likely to occur, allowing police forces to reduce crime (2009). Other companies use database programs like Oracle software to gather data. A Midwest grocery store chain used this to help them understand local buying patterns. They found that males are more likely to buy diapers on Thursday’s and Saturday’s along with beer. They also found that the same shoppers were more likely to complete their weekly shopping on Saturday’s, while Thursday’s, they only picked up a few items. This allowed them to adjust a few of store’s patterns such as moving diapers closer to the beer and ensuring that neither product was on sale on Thursday’s. Companies like Google and Amazon also use the internet to target consumers with advertisements. Amazon uses browsing data on their servers to help target consumers with advertisements. They also use complex algorithms to help identify which advertisements to put on your browser while searching their website and others. Because of their success, many companies are looking to either develop their own method of doing this or acquire the data from Amazon. Contrast this method to Google, they gather data via scanning Gmail e-mails to target advertisements. They also gather data based upon searches, YouTube, which phone numbers that are called using an Android phone, and even the physical location of the user. Many users also feel that they have no control over how Google collects their data. As the Midwest grocery store, Amazon, many police forces, and even Google, the data produced by data mining is generally accurate. In regards to Amazon however, if you have several users that use the same computer or even using the same internet connection, advertisements for a wife who was searching for cooking pots could appear on the husband’s browsing as he looks for a Camelbak for when he runs. Also, if habits change, it might take a few weeks before a store can adapt to the new pattern. As mentioned before, there are some privacy concerns. Google is forefront in the concerns for data mining. As they collect every bit of data created by a user, the extreme lack of privacy is a massive concern for many. While the terms of service states that they do this, many users agree to terms of use blindly. Many do not read what they agree to. In one of the latest suit against Google, it is alleged that Google “intercepts, obtains and uses personal information it collections from emails sent to Gmail users, and his argument holds on the fact that, as he is not a Gmail user, he was never asked to accept and abide by any terms of services Gmail subjects its users to” (Huysman, 2012). Google however responds with that no human reads the e-mail and that they only scan for key words, such as if a user is sending a lot of e-mails about camera equipment. However, there is still an expectation of privacy by many users. This lawsuit states that Google is in violation of California’s privacy laws and Federal wiretapping statutes. Other concerns is that the data collected is sold to other companies. Many fear that telemarketers will call them at the dinner table because their private data was sold to other companies. Many also are concerned that their data will be stolen or lost. Over the last few years, there have been many news reports of databases being hacked or laptops with social security numbers being stolen. Other concerns is how Facebook for example gathers data on millions of users. This data is used to target users, like Amazon does. Overall, data mining is a powerful tool for businesses to develop their product and use the information to target consumers. From Amazon, Google, and Facebook to how grocery stores use the information to target the sales and product locations, the data can be used in many ways. While consumers still have to ensure that their data remains within the company, the risks that consumers will have issues often do not outweigh the benefits of data mining programs.

References
Associated Press. (2013, Sep 05). Google seeks to dismiss Gmail privacy lawsuit, says it has right to scan correspondence. Retrieved from The Washington Post: http://www.washingtonpost.com/national/google-seeks-to-dismiss-gmail-privacy-lawsuit-says-it-has-right-to-scan-correspondence/2013/09/05/0cae68d0-1607-11e3-961c-f22d3aaf19ab_story.html
Converting Data into Business Value at Volvo. (2011, January). Retrieved from Strayer : https://blackboard.strayer.edu/bbcswebdav/institution/CIS/500/1124/Week3-1124/CIS500CaseStudy1-Volvo.pdf
Facebook. (2013, Sep 08). Facebook. Retrieved from Facebook: http://www.facebook.com
Godown, J. (2009, Aug 08). The CompStat Process: Four Principles for Managing Crime Reduction. Retrieved from The Police Chief: http://www.policechiefmagazine.org/magazine/index.cfm?fuseaction=display&article_id=1859&issue_id=82009
Google Research. (N.D.). Data Mining . Retrieved from Google: http://research.google.com/pubs/DataMining.html
Huysman, M. (2012, Oct 09). Google Sued Over Gmail Scanning. Retrieved from International Business Times: http://www.ibtimes.co.uk/articles/392519/20121009/google-gmail-lawsuit-privacy-email-scanning-infringement.htm
Leber, J. (2013, Jan 21). Amazon Woos Advertisers with What It Knows about Consumers. Retrieved from MIT Technology Review: http://www.technologyreview.com/news/509471/amazon-woos-advertisers-with-what-it-knows-about-consumers/
Mendoza, M. (N.D.). Google Says Scanning Text Of Your Emails To Sell Ads Is Perfectly Legal. Retrieved from Talking Points Memo: http://idealab.talkingpointsmemo.com/2013/09/google-says-scanning-text-of-your-emails-to-sell-ads-is-perfectly-legal.php
Microsoft. (2011). Data Mining Helps You Make Better Decisions. Retrieved from Microsoft Business: http://www.microsoft.com/business/en-us/resources/technology/business-software/Data-Mining-Helps-You-Make-Better-Decisions.aspx?fbid=wZAi_33iT_F
Microsoft. (N.D.). Testing and Validation (Data Mining). Retrieved from SQL Server 2012: http://technet.microsoft.com/en-us/library/ms174493.aspx
Miller, D. (2012, Oct 17). Google: Let Us Opt Out of Your Data Mining Machine. Retrieved from Wired: http://www.wired.com/insights/2012/10/google-opt-out/
Oracle. (N.D.). Oracle Data Mining Concepts . Retrieved from Oracle: http://docs.oracle.com/html/B14339_01/1intro.htm
Patterson, L. (2010, Apr 27). The Nine Most Common Data Mining Techniques Used in Predictive Analytics. Retrieved from Marking Profs: http://www.marketingprofs.com/articles/2010/3567/the-nine-most-common-data-mining-techniques-used-in-predictive-analytics
Scott, N. (2000, July 24). Data Mining Can Help Businesses Strike Gold. Retrieved from Sun Sentinel: http://articles.sun-sentinel.com/2000-07-24/business/0007210660_1_data-mining-customer-information-patterns
Turban, E., Volonino, L., Pipior, J., & Wood, G. (2011). Information Technology for Management Improving Strategic and Operational Performance. Hoboken, NJ: John Wiley & Sons, Inc.
University of California, Los Angeles. (N.D). Data Mining: What is Data Mining? Retrieved from University of California, Los Angeles: http://www.anderson.ucla.edu/faculty/jason.frand/teacher/technologies/palace/datamining.htm

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