Robert is a strategic planner for a consulting firm. He receives countless reports for daily analysis, but he avoids being inundated with information by selecting only the few reports that actually serve his purpose. Which principle of data characterization is Robert following?

The correct answer is: Information should be just barely sufficient for its purpose.

Explanation:

Data characterization refers to the general characteristics of objects in a target class, and produces what are called characteristic rules. The relevant data for a class specified by the user is normally retrieved through a database query and executed through a summary module to extract the essence of the data at different levels of abstractions. For example, one may want to characterize OurVideoStore customers who regularly rent more than 30 movies a year. With conceptual hierarchies in the attributes that describe the target class, the attribute-oriented induction method can be used, for example, to perform the data summary. Note that with a data cube that contains a data summary, simple OLAP operations fit the purpose of data characterization.

A) Information should be just barely sufficient for its purpose.

Explanation:

When companies possess large databases with unorganized and purposeless data, that information is useless.

In this case, Roberto is facing a similar problem because he receives a lot of data (countless reports on a daily basis) but most of it is useless since it doesn't serve his purpose. That is why he filters the reports to eliminate the useless ones (which are a majority) and only pays attention to those that can be useful to him.