Part I of this series (August 2003 issue of DM Review) reviewed the work in network analysis of complex systems, particularly the recent research into the small-world (SW) property, aristocratic-egalitarian (A-E) distinction and tipping points. Insights are popping up in strange places. Scientists from anthropology to zoology are making significant progress in understanding their particular complex systems by applying these concepts. These systems have a surprising efficiency interconnecting elements, along with unanticipated tipping points caused by minor stimuli. Understanding the underlying structure of interactions among numerous elements is the determining factor to explaining and even predicting system behavior.
This installment concentrates on the implications to the business intelligence (BI) and data warehousing (DW) fields. In particular, how can the concepts of the SW property help us understand the data in our enterprise data warehouse? Additionally, how can we leverage those insights to solve practical problems?
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