In predictive analytics, the type of data processed includes historical data, which helps identify patterns and trends. This data can come from various sources, like customer transactions, website interactions, and sensor data. By analyzing this historical information, predictive models can be developed to forecast future outcomes or behaviors, such as customer churn or demand for products. Additionally, other data types like demographic and social data may be integrated to enhance the accuracy of predictions. The ultimate goal is to enable organizations to make informed decisions based on anticipated future scenarios.