Data-driven decision support systems (DSS) are computer-based systems that assist users in making better decisions and solving problems. Characteristics of DSS will vary depending on the type of system. Many common characteristics of DSS include flexibility, interactivity, and easy access to data. However, there is one characteristic that is typically not associated with DSS: a lack of user intervention.

Many DSS systems rely on user input or interaction in order to be effective. Therefore, a lack of user intervention can be viewed as a non-characteristic of DSS. Without user input, these systems are unable to properly analyze data and provide users with the insights they need to make effective decisions. As such, user intervention is a necessary component of a successful DSS system.

Other common characteristics of DSS systems include adaptiveness, the ability to actively process data, and the integration of multiple sources of information. These characteristics allow DSS systems to provide users with comprehensive and up-to-date insights into the data. Furthermore, the system must be able to provide users with the tools they need to make decisions quickly and effectively.

In conclusion, a lack of user intervention is not a characteristic associated with DSS systems. Instead, these systems rely on user input and interactivity in order to be effective. By understanding the key characteristics of a successful DSS system, users can maximize the potential of these systems to help their decision-making process.