Enhancing Data Preparation Processes Using Triggers For Active Datawarehousing

Data preparation is a significant preprocessing task to prepare data for mining. The data mining process cannot succeed without a serious effort to prepare data. Very often mistakes are found in data, thus making the analysis process more difficult. Without the data preparation phase, we will have no idea whether the data quality can support analysis queries. Several techniques exist for data preparation in data warehousing. However, one of the problems of existing approaches is their limited support for data preparation for active and changing environments such as Active Data Warehouses. Their focus is on static data preparation approaches. This paper addresses this limitation and a trigger mechanism designed to manage changes in a dynamic environment is utilized. The specification language of a trigger supports active and dynamic capabilities that enable users to automatically filter or select and cleanse data at runtime. In additional the focal point of this work is not only on syntactic but also semantic data preparation approach.