Which of the following analytics types uses historical data explicitly to provide actionable insights?

The correct answer, predictive analytics, focuses on the analysis of historical data to make forecasts or predictions about future events or behaviors. By utilizing statistical algorithms and machine learning techniques on historical datasets, predictive analytics identifies patterns and trends that are valuable for decision-making processes.

This type of analytics does not merely describe what has happened in the past (as descriptive analytics does) but rather extends this analysis to forecast what might happen in the future based on the identified trends. For instance, a retail company might use predictive analytics to determine which products are likely to see increased demand in the upcoming season based on sales data from previous years.

Descriptive analytics simply summarizes historical data, revealing trends and patterns without predicting future outcomes. Diagnostic analytics, on the other hand, investigates data to understand the reasons behind past outcomes. Prescriptive analytics goes a step further by recommending actions based on predictive models but does not inherently focus on analyzing historical data for actionable insights. Predictive analytics uniquely combines the use of past data while aiming to generate actionable insights for future scenarios, making it an essential tool for strategic planning and decision-making.