Data mining and major issues and threats related to privacy
One of the general practices of business intelligence is data mining that mainly involves examining and re-examining the existing databases and large volumes of data so that correlations and patterns can be outlined. Managing vast chunks of data might be challenging for firms, and data mining can ensure the generation of revenue and improved trust with customers by managing and handling sensitive information (Rajaraman & Ullman, 2011). Nevertheless, it is likely for individuals or ordinary citizens of the nation to face privacy issues. Data is often mismanaged, and performance or interaction centric issues take place.
Understanding the privacy-related issues
One of the fundamental rights of an individual is privacy, and the person must receive complete privacy of personal information. However, nowadays, threats and privacy concerns are rising due to the mismanagement of data by the “Knowledge Discovery and Data Mining” (KDDM). The fundamental privacy-centric issues are granulated access to data or private information of customers, management of misinformation, derivative use of information that is unnecessary (Brankovic & Estivill-Castro, 1999). Again, policies, procedures, and laws are not applicable in all cases, and it results in a violation of rights.
Granulated access- Granulated access to sudden sensitive information is another violation of privacy laws in the U.S. For example, certain employers wish to know the personal details of employees such as dietary habits and lifestyle patterns that might be entirely irrelevant for the position he/she is applying for. Hence, access to such information should be strictly denied.
Managing misinformation- Handling or management of misinformation might cause long-term damage to an individual. Misinformation about someone is far more dangerous as it can be harmful to the individual. For example, an individual might get convicted in the court as evidence suggests that the person was carrying drugs and exporting it to another nation. It would permanently damage the reputation of the individual.
Secondary use of data– The KDDM tools might wrongfully expose the sensitive and confidential information because of its exploratory nature. It is unethical to expose an individual’s information for unnecessary purposes. For instance, KDDM tools expose banking, personal details, address, and contact information of individuals, and it might do so for irrelevant purposes. The risk of getting exposed is always present in data mining, and it directly invades the privacy of the concerned individual (Clifton, Kantarcioglu & Vaidya, 2002). Unauthorized access to the personal details of someone is becoming a serious concern that requires the immediate attention of policy developers.
Effects of the issues
It is evident that data mining and privacy threats have already caused damage to the common people, and the harmful impact of KDDM tools must be managed without much delay. However, scholars and experts in this field or government authorities believe that access to personal information of citizens is essential to understand trends and behavior. It would also help in future analysis, and they require detailed information such as name, address, contact details, account details, etc. Nevertheless, privacy threats are hampering the trust of customers in organizations.