It is important to note that the benefits of data mining are numerous, not only for businesses, not-for-profits, and governments, but also for individuals and society as a whole. "Mining for gold is only successful if you're sitting on a gold mine. And unlike a real gold mine, this one you can create yourself" (Maciag 2001, p. 37). Unfortunately, the social, ethical, and legal concerns created by data mining and the associated fears often raise questions about its use. If a middle ground can be reached that protects customers' privacy and ensures security without limiting the power of data mining, both consumers and business could enjoy substantial benefits.
With increasing ease, companies are able to collect vast quantities of data on current and potential customers. Data collected online can now tell decision-makers how customers search for products and services, how they navigate and traverse the Web and what products and services they purchase or fail to purchase. Coupling this data with information from legacy systems provides decision-makers with information concerning trends and patterns previously untapped. The advent of data mining opens up a number of interesting prospects to increase the competitiveness of a firm. In this volatile time, to remain competitive, a corporation must strategically manage its information and react quicker than its competitors. However, this information must be kept secure, but accessible. Every organization must be held responsible for ensuring that its data is being used in a legal and ethical manner. At the same time, organizations must remain competitive, and transforming their data into knowledge is a way to better serve their customers. As it becomes increasingly easy for businesses to gather personal information, individuals must demand and use information countermeasures to control who has access to their information and how it is used. After having read about the social, ethical, and legal issues of data mining, one should understand that there are a number of policy decisions that must be made prior to data mining.