Differentially private processes have some valuable properties. The first, and perhaps most important, is that no amount of post processing or additional knowledge can break the guarantees of differential privacy. This isn’t true for other data anonymization techniques, e.g. k-anonymity. Additionally, differentially private data can be combined with other differentially private data without losing its protection. In practice this means data protected by a process with differential privacy cannot be reverse engineered, re-identified, or otherwise compromised, no matter the adversary.