Abstract: This work addresses data warehouse (DW) maintenance, how changes to autonomous, heterogeneous and distributed sources should be detected and propagated to a warehouse. The research suggested that backup and recovery is very important and critical issues in DW maintenance. A data warehouse stores integrated information as materialized views over data from one or more remote sources. These materialized views must be maintained in response to actual relation updates in the remote sources. Based on whether the current materialized views will be used in computing the new views and whether the data warehouse will query the remote data sources for additional data to do the computation, the data warehouse view maintenance techniques are classified into four major categories: self-maintainable re-computation, not self-maintainable re-computation, self-maintainable incremental maintenance and not self-maintainable incremental maintenance. It also has mainly addressed issues relating to the internal operation of data warehouse servers. Work related to data warehouse maintenance has received less attention and only a limited set of maintenance alternatives are considered while ignoring the autonomy and heterogeneity of sources and finally we proposed a future work.