What distinguishes descriptive analytics from predictive analytics?

Descriptive analytics is specifically designed to summarize and analyze historical data, providing insights into what has happened over a given period. It focuses on interpreting past events and trends, helping organizations understand their historical performance through reports, visualizations, and data summaries. By highlighting key metrics and trends, descriptive analytics lays the foundation for further analysis, including predictive analytics.

In contrast, predictive analytics is concerned with forecasting future outcomes based on historical patterns and metrics. It uses statistical models and machine learning techniques to anticipate potential future scenarios, drawing on past data as a reference, rather than simply summarizing it. Options that connect predictive analytics with real-time data or historical patterns do not accurately describe descriptive analytics, which fundamentally revolves around past data analysis rather than future predictions or ongoing data assessments.