Which statement correctly defines prescriptive analytics?

Prescriptive analytics is fundamentally about providing actionable recommendations based on data analysis. It goes beyond merely analyzing what has happened or predicting what is likely to happen in the future. The key aspect of prescriptive analytics is its ability to suggest specific courses of action that can help achieve desired outcomes. This could involve utilizing optimization algorithms, simulations, or decision trees to guide decision-making processes based on data insights.

The distinction from the other concepts is clear: while explaining why events occurred offers insight into past occurrences, and predicting trends forecasts what might happen next, prescriptive analytics focuses directly on what actions should be taken to achieve the best results moving forward. Summarizing historical occurrences is about aggregation of data without offering any future actions, which does not fit within the scope of prescriptive analytics. Therefore, the option that emphasizes recommendation for actions aligns perfectly with the definition and purpose of prescriptive analytics.