This article provides a complete review on new perspectives and systematic interpretations of published literatures by painstakingly organising them into subcategories. [This article] [gives] [a] comprehensive overview on new perspectives and this is accomplished by supplying a list of the various pieces of published literature. This article discusses the fundamental ideas behind the numerous existing data mining methods that protect users' privacy, as well as the benefits and drawbacks associated with these technologies. The techniques that are currently available for protecting the privacy of users during data mining can be categorised according to various aspects. These aspects include things like distortion, association rule, hide association rule, taxonomy, clustering, associative classification, outsourced data mining, distributed, and k-anonymity. The most salient advantages and disadvantages of the procedures are outlined here within their respective categories. This in-depth investigation highlights the historical development, the research issues that are occurring at the present time, the future tendencies, the gaps, and the deficiencies. It has been decided that obligatory additional significant changes must be implemented for the purpose of providing stronger protection and preservation of personal privacy