A great example to highlight would be how Power BI handles these concerns. Power BI allows you to implement Row-Level Security (RLS) to ensure users only see data that is relevant to them. It also supports encryption for data at rest and in transit, which is crucial for safeguarding sensitive information. Additionally, Power BI offers tools like sensitivity labels to classify data and restrict access, along with audit logs that track user activities, ensuring full transparency and compliance with security protocols.

Publishing data in Restricted workspace and giving limited access for it. Trying Row level security can also help in projecting the data Password protecting excels will also be one of the solutions

Safeguarding data in design while maintaining creativity requires a careful balance between aesthetics and security. Removing identifiable details in visual data (e.g., using pseudonyms or aggregated data) can be useful. One should protect data files and communication channels used for visual design with strong encryption. I would also restrict access to sensitive data, ensuring only authorized personnel are involved in the design process. I think one should use only the necessary data, avoiding unnecessary inclusion of sensitive information. It's important to substitute real data with synthetic or sample datasets during design.

One way to ensure data privacy and security in data visualization is by using strong authentication factors. Start with dual authentication, which requires a password and a passcode. For even more security, use multi-factor authentication (MFA), which can include a fingerprint or face scan. Also, ensure data access is restricted to only those who need it, and regularly review permissions to avoid any data breaches.