Final answer:
Global differential privacy is falsely claimed to be added after data is collected; rather, it's part of the data collection and analysis process, ensuring individual data privacy.
Step-by-step explanation:
The statement that global differential privacy is added after data is collected is false. Differential privacy is a statistical technique that is applied to data aggregation and analysis processes to ensure that the privacy of individual data entries in a database is protected. Instead of being added post-collection, it's an integral part of the data collection and analysis pipeline. It works by adding a certain amount of noise to the data or to the analysis queries to ensure that the outcomes cannot be traced back to individual data subjects. This noise is calibrated in a way that preserves the utility of the data while still providing rigorous privacy guarantees.