Data Mining in Data Warehouses

Data warehouses provide an integrated environment where huge amounts of data extracted from operational sources are available for various kinds of decision support analysis. Hence, in order to allow the user to improve the quality of the performed analysis, it is becoming of fundamental importance to effectively integrate mining capabilities and data warehousing technology. This paper describes AMORE-DW an integrated environment for the specification of data mining requests and the extraction of association rules from a data warehouse. The adopted architecture is characterized by a tight coupling of data mining with the relational OLAP (ROLAP) server on the data warehouse that provides efficient access to the data to be analyzed. The main issues faced during the design are presented and the trade-off between flexible data analysis and system performance is discussed.