Decision Support Systems for Business Intelligence, Second Edition

Chapter 4. MODEL COMPONENT

Business Intelligence allows decision makers to have a better understanding of the context of their choices. It is based upon the collection and examination of information called "analytics." Analytics are the result of some kind of modeling of (usually) historical data that generally includes the application of statistical analysis, operations research, or other quantitative tool for the purpose of either explaining what is or predicting what will be. The purpose of the model is to represent critical relationships in such a way to guide decision makers toward a desired goal. The involvement and support of these models is what differentiates DSS from other kinds of computerized systems. Said differently, without a model, a system is not a DSS. Hence, to understand DSS, one must understand models. Unfortunately, in practice, modeling, and especially model management, is the least developed of the aspects of DSS.

MODELS AND ANALYTICS

Modeling is the simplification of some phenomenon for the purpose of understanding its behavior. Even before the tsunami of data began hitting organizations, modeling provided a structure for understanding and predicting events. Modeling simplifies and abstracts detailed event data to allow understanding of the major forces acting upon the alternatives. It involves a process of summarizing and accumulating of data. In addition, modeling involves a process of removing unnecessary detail, thereby allowing the important patterns ...