A metadatabase-enabled executive information system (part B): methods for dynamic multidimensional data analysis

In tandem with the growth of the Internet and e-business, the number of digital data sources has increased immensely. These data sources contain important transactional data and are generally interconnected via a network. This has created a pressing need for a suitable executive information system (EIS) that is capable of extracting data from internal and external data sources and providing data analysis on demand for business executives. On-demand data analysis requires an information integration approach that can manage rapid changes in data sources. Existing EISs commonly adopt data warehousing technology to consolidate data from multiple sources in a tailor-made fashion, and support predefined multidimensional data analysis. However, this architecture is neither adaptable to changes in local sources nor flexible enough for ad hoc analyses. This paper develops methods and algorithms for a new EIS architecture that takes advantage of a metadatabase to achieve adaptability and flexibility. A PC-based prototype is built to prove the concept.