Using intelligent agents to identify trends in multi-dimensional databases

The widespread use of relational and other database technologies has given rise to enormous data stores, in both private and government organisations. Faced with these vast data stores, many organisations have seen the need for sophisticated analytical tools that allow users to view summary data from any required perspective. This need has been met, in part, by the development of Multi-Dimensional Data Bases (MDDBs) and associated On-Line Analytical Processing (OLAP) tools. MDDBs extract data from conventional databases and store it in partially aggregated form, while OLAP tools allow users to manipulate that aggregated data with ease. Such manipulation includes the ability to select: the factors (or Dimensions) to be included in a summary display, the categories (or Members) within each Dimension to be included in the display and the level of aggregation of data in the display.