Part 1 of this article (August 2003 issue of DM Review) reviews 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. Part 2 (September 2003 issue of DM Review) applies these concepts to the business intelligence (BI) and data warehousing (DW) fields with a new methodology called Associative Link Analysis (ALA) by discussing the translation of typical warehouse schema into an associative graph form. This article, the final in the series, describes several metrics for analyzing graphs, strategies and tactics based on the SW property, and implementation issues.

The next step is the analysis of the graph structures generated from the warehouse schema. Many of the metrics (or analytics) for characterizing graph structures have emerged from work in the social network analysis (SNA) field that studies interactions among people in terms of friendship, marriages, authority, citations and the like.1 Within the context of any business system, associations will have a social basis even though the unit of analysis may not be a person but an object (e.g., product) or event (e.g., sales transaction). Following are several metrics that can give practical insights into nature of these graphs.2

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