Why does data mining usually focus on groups instead of specific individuals?

In computer science, data mining is primarily focused on groups rather than specific individuals because its core purpose is to discover general, useful patterns and relationships within large data sets.

Businesses and organizations typically prioritize broad insights over individual records to improve outcomes at scale. For example, a retailer is generally more interested in identifying purchasing trends across a large customer base to optimize sales than in tracking the specific habits of a single person.1

Focusing on groups also serves as a critical safeguard for privacy. Because commercial and government databases often contain sensitive personal information, prioritizing general knowledge helps mitigate the risks of unwarranted intrusion, abuse, or unauthorized disclosure of private records. While pattern analysis can be used to detect anomalous individual behavior, such as fraud or criminal activity, the ethical standard in the field increasingly emphasizes the development of privacy-preserving techniques to protect individual data from exposure.12