Differential privacy is increasingly vital in modern data analysis because of the sheer volume of personal data being collected and analysed. With advancements in technology, personal data is used for various purposes, from improving healthcare to tailoring marketing strategies. However, this raises significant privacy concerns. Differential privacy addresses these concerns by providing a way to gain valuable insights from data while protecting individual privacy. It's crucial in scenarios where sensitive information, like medical records or financial data, is analysed. By ensuring that the output of data analysis does not reveal individual data, differential privacy helps maintain trust in data-driven processes and complies with stringent privacy regulations.