The Data warehouse (DW) has become the essential component of almost every modern enterprise information system. It is proposed to collect and store heterogeneous and bulky data. DW represents a collection of thematic, integrated, non-volatile and histories data. It is feds from different data sources and it is highly required of the system to respond to complex online analytical queries. Generally, the analytical queries execution cost on large tables is very high. Reducing this cost becomes essential to enable decision-makers to interact in a reasonable time. In this context, different optimization techniques such as fragmentation, indexing, materialized views, and parallelism are used. On the other hand, the volume of data residing in the DW is constantly evolving. This can increase the complexity of frequent queries, which can degrade the performance of DW. The administrator always has to manually improve the DW performance from the new load of frequent queries. Distance Administration of DW through the web becomes important. The approach proposed in this paper aims at an incremental horizontal fragmentation technique assisted with temporary materialized view through a web service. This technique is based on managing the temporary materialized view in order to optimize the new frequent queries before proceeding on the implementation of the fragmentation. An experimental study on a real DW is carried out and comparative tests show the satisfaction of our approach.
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