What technique can be used to safeguard sensitive information in Power BI reports?

Using row-level security and data masking is a robust technique for safeguarding sensitive information in Power BI reports. Row-level security (RLS) enables you to restrict data access to specific users based on their roles, ensuring that individuals only see data pertinent to their authorization level. This is crucial when dealing with sensitive or confidential data, allowing you to implement fine-grained data visibility controls.

Data masking complements RLS by obscuring sensitive information within reports, so while authorized users can access certain datasets, they do not see confidential details. For example, sensitive personal identifiers can be masked so that users can still make informed decisions based on available data without exposing confidential information.

Other techniques listed, such as data importing, cloud storage, and using filters only, do not inherently provide the necessary level of protection for sensitive information. Data importing is merely a method of bringing data into Power BI; it does not control access once the data is in the report. Cloud storage offers availability and accessibility but does not secure data from unauthorized users. Filters can limit the data displayed in reports but do not provide the same comprehensive protection as RLS and data masking. This makes row-level security and data masking the most effective technique for safeguarding sensitive information in Power BI.