The main focus of privacy preserving data publishing was to enhance traditional data mining techniques for masking sensitive information through data modification. The major issues were how to modify the data and how to recover the data mining result from the altered data. The reports were often tightly coupled with the data mining algorithms under consideration. Privacy preserving data publishing focuses on techniques for publishing data, not techniques for data mining. In case, it is expected that standard data mining techniques are applied on the published data. Anonymization of the data is done by hiding the identity of record owners, whereas privacy preserving data mining seeks to directly belie the sensitive data. This survey carries out the various privacy preservation techniques and algorithms.