Randomisation is central to differential privacy, serving as the mechanism that protects individual data points within a dataset. By introducing randomness in the data analysis process, differential privacy ensures that the impact of any single individual's data on the overall analysis is minimised. This randomness creates uncertainty about the presence or absence of specific data points, thus preserving individual privacy. Randomisation provides a way to balance the extraction of useful insights from a dataset with the need to protect sensitive information, ensuring that personal data cannot be easily isolated or identified.