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Data mining is a huge industry that intrudes in the lives of society by gathering information on individuals legally but without knowledge or consent. As Yu-Chin Lin explains in his article "A New Approach to Generate Patterns from Enterprise Databases" in Notes in Computer Science, data mining is a business that thrives on opportunity, taking advantage where it sees fit, recording online transactions, internet histories, and buying spending habits from retailers.
Not only do data companies collect sensitive data, but they also collect birthdates, height, eye and hair color, current and former addresses, religion, criminal and arrest records, sexual preference, friends and relatives, medical conditions and more.
This data is cross checked several times and entered into databases where it is stored along with millions of other entrants Lin Data mining companies, that collect information on individuals, sell the information in such forms as background checks and personal information portfolios.
Companies that buy this information the most include banks, insurance companies, law firms, the media, marketers, private investigators, and law enforcement and other government agencies.
There are problems with having a large amount of private data on a consumer. The data is not always stored in a secure location and is susceptible to hack and information loss. The data is stored in large amounts with several individuals in a central location; once a hacker is in, he has access to several hundreds of thousands of "pages" of data.
These data companies are not listening to anyone but their lawyers on how they should protect and store the data they collect. Data mining is becoming a large business and has the potential to get out of control. The Federal government should implement regulations on the collection of data, notifying individuals about their data, and the usage of private data once collected.
Companies that collect data argue that data collection is not illegal and that they safeguard their material effectively against data theft and loss.
The article "Commercial Personal Data Collection" from Issues and Controversies explains that data collection companies are "generally interested in safeguarding it [the data] to the best of their abilities.
Companies will do whatever is necessary to keep their image and value intact" "Commercial". Companies who are public and have shareholders need to maintain a business image. When data mining companies have large security breaches the shareholders view this as a weakness in the company and sell the stock.
This drops the value of the company and presents the company in a bad light.
All businesses want their stock to be rising because it shows positive growth in the company. Like all businesses data collection companies strive to maintain a positive image. Data loss presents a negative image for data mining companies and is a sign of bad business.
Data mining companies will protect their information as much as necessary to maintain positive growth and good business.
Many critics also reply that consumers have a choice as to how much information they allow for companies to collect. They suggest that people who are worried about data mining of their credit histories can choose to not rely on credit cards as much for their financial transactions.
Data mining companies believe that consumers have the right to regulate their own personal data and that consumer awareness is important. Data collection companies state, that consumer awareness can help control how much data a user allows to be mined.
Another problem opponents believe regulating commercial data collection will have, is that it infringes on the freedom of speech.
Assuming that consumers have a certain amount of choice in how much information they reveal, critics say that regulating commercial speech of data companies would be unnecessary. Data mining companies do not believe that data collection is the problem, but that hackers and frauds are the cause of controversy in their field.
In recent years, the following companies had a significant loss of data in the form of hackers, lost laptops, lost disks, and backup tapes: Department of Justice with 80, entries, Choice Point withentries, University of Texas withentries, Marines withentries, Time Warner withentries, Bank of America with 1, entries, Citi Group with 3, entries, and the Department of Veterans with 26, entries lost Big Brother.
These large data breaches are not small figures.big essay on global warming Ideal approaches section: behaviourist essay, twin studies, defence mechanisms causes of the civil war essay apush abhijnanasakuntalam critical essays on hamlet history of the computer essay how to make ppt of research paper cefalea cortazar analysis essay the storyteller mario vargas llosa analysis essay the id ego and superego essay about myself curriculum .
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Introduction to data warehousing and data mining. Suyog Dhokpande, Hitesh raut This paper describes about the basic architecture of data warehousing, its software and process of data warehousing. It also presents different tech- Introduction to data warehousing and data mining. Research papers in data mining and data warehousing.
Research papers in data mining and data warehousing. 0 Comment. Usm vs essays the house of the future essays preventing water pollution essay in english oxbridge essays dissertations.
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Data Management: Data Warehousing and Data Mining Research Paper Since both acquisition (data mining) and storage (data warehousing) have become much simpler, most of the interest in business analytics today revolves around what to do with Big Data.