Which example best represents effective data mining?

Effective data mining involves discovering patterns and insights from large datasets that can inform strategic decisions, enhance targeting, and improve business outcomes. Profiling customers based on their usage characteristics is a prime example of this.

By analyzing data to understand customers' behaviors, preferences, and habits, organizations can tailor their marketing strategies, enhance customer satisfaction, and increase retention rates. This approach goes beyond simple summaries or calculations; it uses sophisticated techniques to extract valuable insights that drive actionable business strategies.

In contrast, the other options focus primarily on historical data analysis or basic calculations, such as determining profit margins, calculating current revenue, or summarizing sales data. While these are useful for reporting and tracking performance, they do not involve the deeper analytical techniques or the predictive insights that characterize effective data mining.