How does Row-Level Security improve data protection in Power BI?

Row-Level Security (RLS) in Power BI restricts the rows of data that a user can see based on their identity, role, or business rules. For example, imagine a company has sales data for India, the US, and the UK. Instead of creating separate reports for every regional manager, a single Power BI report can use RLS so that: The India manager sees only India data. The US manager sees only US data. The UK manager sees only UK data. Senior management can see all regions. RLS is generally implemented by creating security roles and defining DAX filters that determine which records are visible to members of those roles. A common enterprise approach is dynamic RLS, where the user's identity is mapped to a security table containing information such as user email address, department, region, or business unit. RLS provides several important advantages: Prevents users from viewing unauthorized records Supports centralized report management Reduces the need to create multiple reports Helps enforce organizational data-access policies Supports multi-department and multi-region reporting However, RLS is not a replacement for complete security architecture. Organizations must also properly secure the underlying data sources, semantic models, workspaces, datasets, and sharing permissions.