What does predictive analytics aim to achieve?

Predictive analytics is primarily focused on using historical data along with statistical algorithms and machine learning techniques to forecast potential future outcomes. It involves analyzing patterns and relationships within the existing data to create models that can estimate future events or behaviors. This approach enables organizations to make informed decisions, anticipate customer needs, and optimize their resources effectively.

While forecasting future outcomes using current data is a part of what predictive analytics does, the emphasis on both historical data and statistical algorithms is what differentiates predictive analytics from other forms of data analysis. The other options relate to different aspects of data analytics, but they either lack the combination of historical data and statistical analysis that defines predictive analytics or focus on present trends without incorporating future forecasts. Thus, the correct understanding aligns closely with the definition, emphasizing the importance of both historical data and statistical algorithms in making accurate predictions about future events.