Approximate Query Answering System Architecture

Business Intelligence is an activity that aims to extract information and knowledge from a central repository, the so-called data warehouse, in order to improve the business processes of an information system. Typical applications are based on reporting, on-line analytical processing, data mining, and approximate query processing. Business Intelligence platforms are software tools that allow to develop such applications. In general, these applications are composed of complex dashboards that provide a synthetic frame to be used in decision making. According to the criteria proposed by the Gartner Group to evaluate Business Intelligence platforms, one of the most important feature is the information delivery strategy, whereby final users can share the environment and access the same resources in real-time. For this reason, more and more traditional vendors include web services along their software packages. At the present time, Web-based platforms focus mainly on the issues related to the applications' deployment on a server. However, platforms that support approximate query processing require a more complex architecture since they generally need to perform a preliminary data reduction process and, then, they require ad hoc metadata. In this paper, the architecture of such a system is presented along with a proposal of standardization of metadata to be used in approximate query processing.