Which term describes analytics that determines potential outcomes based on current and past data?

Predictive analytics is the term that focuses on using current and historical data to forecast future outcomes. It employs statistical techniques and machine learning algorithms to identify patterns and trends within data, which allows organizations to make informed decisions about potential future scenarios.

This type of analytics goes beyond merely examining past performance or identifying causative factors; it actively seeks to estimate what is likely to happen based on the insights gained from historical data. By leveraging predictive models, businesses can proactively address potential challenges or capitalize on upcoming opportunities, ultimately enhancing their strategic planning and decision-making processes.

Descriptive analytics, in contrast, provides a summary of historical data, outlining what has happened without making any predictions about future events. Diagnostic analytics digs deeper into data to understand the reasons behind past outcomes. Prescriptive analytics, on the other hand, focuses on recommending actions to achieve specific outcomes, but it does not directly estimate what will occur in the future. Thus, predictive analytics is distinct in its aim to provide insights into potential future events grounded in the analysis of past and present data.