  A data warehouse is a large data repository for the purpose of analysis and
decision making in organizations. To improve the query performance and to get
fast access to the data, data is stored as materialized views (MV) in the data
warehouse. When data at source gets updated, the materialized views also need
to be updated. In this paper, we focus on the problem of maintenance of these
materialized views and address the issue of finding such auxiliary views (AV)
that together with the materialized views make the data self-maintainable and
take minimal space. We propose an algorithm that uses key and referential
constraints which reduces the total number of tuples in auxiliary views and
uses idea of information sharing between these auxiliary views to further
reduce number of auxiliary views.
