What's the safest way to handle sensitive data when it needs to be shared or tested?

When learning about cybersecurity basics, one area I keep coming back to is how sensitive data should be handled when it needs to be used outside of its original environment.

For example, in development or testing, real user data can be useful because it reflects real behavior and helps identify issues more accurately. At the same time, using that same data outside of production creates obvious risks if it is not properly protected.

I’ve seen a few general approaches mentioned, such as removing personal identifiers, masking specific fields, or using completely synthetic datasets instead of real information. However, I’m not sure what is generally considered the safest or most widely recommended approach in practice.

For people who are familiar with cybersecurity or privacy fundamentals, what is the correct way to think about this problem? Are there standard practices that beginners should follow when dealing with sensitive data in non-production environments?