Demand for Business Intelligence (BI) applications continues to grow even at a time when demand for most information technology (IT) products is soft. Yet,information systems (IS) research in this field is, to put it charitably, sparse.
While the term Business Intelligence is relatively new, computer-based business intelligence systems appeared, in one guise or other, close to forty years ago.1 BI as a term replaced decision support, executive information systems, and management information systems [Thomsen, 2003]. With each new iteration, capabilities increased as enterprises grew ever-more sophisticated in their computational and analytical needs and as computer hardware and software matured. In this paper BI systems are defined as follows:
BI systems combine data gathering, data storage, and knowledge management with analytical tools to present complex internal and competitive information to planners and decision makers.
Implicit in this definition is the idea (perhaps the ideal) that business intelligence systems provide actionable information delivered at the right time, at the right location, and in the right form to assist decision makers. The objective is to improve the timeliness and quality of inputs to the decision process, hence facilitating managerial work.

Common Features

Sometimes business intelligence refers to on-line decision making, that is, instant response. Most of the time, it refers to shrinking the time frame so that the intelligence is still useful to the decision maker when the decision time comes. In all cases, use of business intelligence is viewed as being proactive. Essential components of proactive BI are:

  • - REAL-TIME DATA WAREHOUSING
  • - DATA MINING
  • - AUTOMATED ANOMALY AND EXECPTION DETECTION
  • - PROACTIVE ALERTING WITH AUTOMATIC RECIPIENT DETERMINATION
  • - SEAMLESS FOLLOW-THROUGH WORKFLOW
  • - AUTOMATIC LEARNING AND REFINEMENT,
  • - GEOGRAPHIC INFORMATION SYSTEMS
  • - DATA VISUALIZATION