1. This example shows the development of a classification tree using DMVis, a data visualisation tool. The tool allows visualisation of relational structures. The example is that of a double glazing estimate database Part of the data model is shown below

2. Visualisation of the whole database of estimates It shows 5 (or 6?) clear groups Cluster A Cluster B Cluster C Cluster D Cluster E Data Base

3. Tool selects Cluster A to visualise separately AB C D E Data Base

4. Visualisation of cluster A shows that it has 4 clear sub clusters A B C D E Data Base A1A2 A3 A4

5. Classification by visualisation The tree produced by use of the visualisation tool showed advantages over other clustering techniques: The resulting classification had a natural hierarchy. The hierarchy had an easily understood basis for human understanding. Problems as to degree of branching ( at the first level, 4 at the second for cluster A ) are easily resolved visually. Long thin trees, such as are produced by a with binary division system, or short fat trees, with too many classes are un-natural, and hard to understand. They frequently need re- structuring. The visualisation method can be applied to relational and recursive database structures, and doesn’t require a single table or query to be identified.