Warehouse views need to be updated when source data changes.  Due to
the constantly increasing size of warehouses and the rapid rates of
change, there is increasing pressure to reduce the time taken for
updating the warehouse views.  In this paper we focus on reducing 
this update window by minimizing the work required to compute and 
install a batch of updates.  Various strategies have been proposed 
in the literature for updating a single warehouse view.  These 
algorithms typically cannot be extended to come up with good 
strategies for updating an entire set of views.  We develop an 
efficient algorithm that selects an optimal update strategy for 
any single warehouse view.  Based on this algorithm, we develop 
an algorithm for selecting strategies to update a set of views.  
The performance of these algorithms is studied with experiments 
involving warehouse views based on TPC-D queries.