Ethical, Security, Legal and Privacy Concerns of Data Mining

Data mining is a powerful new technology with great potential to help companies focus on the most important information in the data they have collected about the behavior of their customers and potential customers. It discovers information within the data that queries and reports can’t effectively reveal.

The amount of raw data stored in corporate databases is exploding. From trillions of point-of-sale transactions and credit card purchases to pixel-by-pixel images of galaxies, databases are now measured in gigabytes and terabytes. Raw data by itself, however, does not provide much information. In today’s fiercely competitive business environment, companies need to rapidly turn these terabytes of raw data into significant insights into their customers and markets to guide their marketing, investment.

Data mining, or knowledge discovery, is the computer-assisted process of digging through and analyzing enormous sets of data and then extracting the meaning of the data. Data mining tools predict behaviors and future trends, allowing businesses to make proactive, knowledge-driven decisions. Data mining tools can answer business questions that traditionally were too time consuming to resolve. They scour databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectations.

Data mining derives its name from the similarities between searching for valuable information in a large database and mining a mountain for a vein of valuable ore. Both processes require either sifting through an immense amount of material, or intelligently probing it to find where the value resides.

Frequently, the data to be mined is first extracted from an enterprise data warehouse into a data mining database or data mart. The data mining database may be a logical rather than a physical subset of your data warehouse.

Ethical Concerns  of Data Mining

The use of data mining, especially data about people, has serious ethical implications. Companies face an ethical dilemma when even deciding if the company should make a person aware his/her information is being stored for future data mining. By giving a person the option to opt out of data collection, a company can hurt its competitive advantage in a market place. A company must decide if a lack of ethical concern will cause a loss in good will from consumers and suffer from a backlash from the company’s consumers. Companies who use data mining techniques must act responsibly by being aware of the ethical issues that are surrounding their particular application; they must also consider the wisdom in what they are doing. For example, data mining sometimes can be used to discriminate people, especially regarding racial, sexual and religious orientations. The use of data mining in this way is not only considered unethical, but also illegal. Individuals need to be protected from any unethical use of their personal information, and before they make any decision to provide their data they need to know how this information will be used, why is it being use, what parts of the information are going to be taken, and what consequences this action will have. By doing this, Individuals will be informed and told straightforwardly about the reasons and consequences of using their information. Ethical concerns in data mining can be seen in two main ethical themes and these relate to privacy and individuality. As mentioned previously, the wrong use of data can cause people to fall in unethical issues, which are also considered illegal. The importance of privacy and individuality has to be valued and believe protected to make sure that people are treated reasonably. People should be conscious of the significance of the threats and dangers and constantly discuss these ethical issues. Experts consider data mining to be morally neutral, on the other hand, the way that this data is being used may come up with questions and concerns about ethics. Data need to be used in the right purpose to make sure people are safe.

Security Concerns  of Data Mining

Data mining is the process of creating a sequence of correct and meaningful queries to extract information from large amounts of data in the database. As we know, data mining techniques can be useful in recovering problems in database security. However, with the growth of development, it has been a serious concern that data mining techniques can cause security problems. A lot of security experts see data mining as one of the most primary challenges that consumers will encounter in the next decade. The definite complexity in data mining is building up accurate models for data analysis without giving the right to use the information in specific customer records, which will secure the database from being used the wrong way. Developing such models can reduce the security issues that users may face. Security problems in data mining are one of the most popular concerns because of the fact that when using data mining individuals are usually working with large amount of information, and they can have access to it easily. This is dangerous if this data was not used in a secure way. As data mining guarantees to open up lots of new fields for extracting information from both old databases and future databases that may be developed with data mining as a support purpose, the data mining session in some large companies suggest that there can be serious security issues in data mining. While saying this, it is not to recommend that data mining should be illuminated, however, it is to mention security as one of important aspects and issues that should be judged and addressed.

Data warehousing companies must monitor who has access to the data within and what parts of the data warehouse they have access to. An example of a company that allows restricted access to their data warehouse for data mining purposes is Wal-Mart. Wal-Mart has a very extensive database of all their stock, stores, and collected data. Companies that have products carried by Wal-Mart are allowed into Wal-Mart’s database. This allows these companies to mine this data for information regarding the sale of their products. By restricting the accessibility of these companies to just the products offered by the companies, Wal-Mart shows that it is aware of the concerns for security and privacy when it comes to data mining.

Legal and Privacy Concerns  of Data Mining

In data mining, the privacy and legal issues that may result are the main keys to the growing conflicts. The ways in which data mining can be used is raising questions regarding privacy. Every year the government and corporate entities gather enormous amounts of information about customers, storing it in data warehouses. Part of the concern is that once data is collected and stored in a data warehouse, who will have access to this information? Oftentimes a consumer may not be aware that the information collected about him/her is not just shared with who collected the information. With the technologies that are available today, data mining can be used to extract data from the data warehouses, finding different information and relationships about customers and making connections based on this extraction, which might put customer’s information and privacy at risk. Data mining necessitates data arrangements that can cover consumer’s information, which may compromise confidentiality and privacy. One way for this to happen is through data aggregation where data is accumulated from different sources and placed together so that they can be analyzed.

Companies such as IBM are working on methods of mining data that will allow for complete individual privacy while still creating accurate models of data. IBM’s method has developed a method called Privacy-Preserving Data Mining. By randomizing a consumer’s personal information before it is ever transmitted using IBM’s Privacy-Preserving Data Mining Method, a company can still gather the information it would like while not impeding on its customer’s right of privacy.

It is logical that a lot of companies and governmental agencies need to use data mining as a part of their jobs, but the hesitation is if this information is being used the right way. For example, data mining can be helpful for some companies in order to target the right market. In the technological and the informational age it looks like the process of getting data about customers and employees is getting a lot easier than it used to be before. The quick transfer of personal information has resulted to identity theft risks. Privacy concerns are becoming an important issue in data mining because of the risks behind it, especially that many of the consumers who buy products or services are not conscious of data mining technology.

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