How is row-level security primarily achieved in a dataset?

Row-level security in a dataset is primarily achieved through role-based user ID mapping in the dataset. This approach allows different users to access only the rows of data that are relevant to them based on their roles or affiliations. By implementing role-based mapping, an organization can dynamically control data visibility within the same dataset, ensuring that sensitive information remains restricted to authorized users while still enabling users to work with the data they need.

This method streamlines data management because rather than duplicating datasets for different users or groups, a single dataset can serve many different user roles, with security applied at the row level based on user identity and associated attributes.

In contrast, while applying user access filters in reports can limit what is visible to users, this often occurs after the data has already been processed, rather than securing it at the dataset level. Predefined groups can help simplify administration of access control, but they do not provide the granular control that role-based mapping facilitates. Creating specific datasets for each user is not practical and can lead to significant inefficiencies, especially in larger organizations, as it complicates data management and increases the potential for errors or oversights.