Cloud computing provides huge storage capacity to store all important and sensitive data as well as process the large data sets. Sensitive data means personal data about a person, which means there is something inside a person that is considered characteristically unique. For example individual people shares private data like bank account details, personal details, health records and financial data. All these private data which are stored in cloud environment needs high security and privacy. In this paper Optimized balanced scheduling is applied to perform anonymization on data sets. Here scheduling is based on the time and the size of the data sets. Anonymization approach provides privacy on individual people personal data. In large data sets it's very difficult to provide anonymizing approach; so two phase top down specialization approach is introduced to provide privacy as well as handling of large data sets in cloud. In first phase, the process of splitting large data sets into small dataset and applying anonymization on individual data sets takes place. In second phase intermediate results are merged into one and further anonymization process is applied to get the desired output. Here anonymization process is implemented using map reduce framework on cloud environment. © 2010 RJPBCS.