What is datamining? What are positives and negatives of datamining?

Linoff & Berry, (2011), asserts that datamining is the extraction of usable data from the available raw data or the process by which companies are able to convert raw data into usable information. Data mining is important since it is an analytical tool since the data previously collected ca be analyzed to predict future market trends hence used to make informed decision based on statistics and facts. In addition, the data can be used to establish a pattern of behavior of consumer or operational needs which can be imperative to improve production hence maximization on profits. Additionally, data mining is an important tool that can be used to detect flaws in operations and activities within an organization hence establish mitigation mechanisms. However, opponents of data mining posit that the privacy of the people used in the data like in consumer behavior is not a guarantee. Data can be bought and shared hence individual people can be identified with their privacy not assured in such third party data usage. In addition, some opponents of the technique argue that the information can be misused for personal reasons as opposed to research work when used by different people or organizations.

References

Linoff, G. S., & Berry, M. J. (2011). Data mining techniques: for marketing, sales, and customer relationship management. John Wiley & Sons.