  With the wide development of databases in general and data warehouses in
particular, it is important to reduce the tasks that a database administrator
must perform manually. The idea of using data mining techniques to extract
useful knowledge for administration from the data themselves has existed for
some years. However, little research has been achieved. The aim of this study
is to search for a way of extracting useful knowledge from stored data to
automatically apply performance optimization techniques, and more particularly
indexing techniques. We have designed a tool that extracts frequent itemsets
from a given workload to compute an index configuration that helps optimizing
data access time. The experiments we performed showed that the index
configurations generated by our tool allowed performance gains of 15% to 25% on
a test database and a test data warehouse.
