Which type of analysis does Einstein Discovery primarily conduct?

Einstein Discovery primarily conducts predictive analysis, focusing on forecasting future outcomes based on historical data patterns. This type of analysis leverages machine learning algorithms to create models that can identify trends and make predictions about what is likely to happen in the future. By analyzing past behaviors and outcomes, Einstein Discovery generates insights that help organizations anticipate future performance metrics and guide decision-making.

The ability to forecast future outcomes is crucial for organizations looking to optimize their strategies and operations. For example, businesses can use Einstein Discovery to predict customer churn, identify sales opportunities, or anticipate market changes, enabling proactive rather than reactive planning.

In contrast, the other options pertain to different types of analysis. Descriptive analysis summarizes historical data, which is useful for creating reports and understanding what has happened in the past. Qualitative analysis focuses on understanding user experiences through subjective insights and interpretations, while quantitative analysis emphasizes numerical data representation and statistical calculations. While these forms of analysis are valuable in their own right, they do not encapsulate the primary functionality of Einstein Discovery, which is dedicated to predictive insights.