3.1 Space

3.2 Data

3.3 Elements

3.4 Interrelations

3.4 Causes and dependencies

Show interrelations: Causes and dependencies

Another form of data density concerns content-related aspects. a Show “everything" when possible, especially extreme values and deviant values: Details increase not only the level of credibility, but comprehension as well. b Comparisons should be shown where possible: This is the main purpose for using charts. c Causes should be shown where possible: Certain causality should be pointed out with charts whenever possible. Charts should be used to prove, explain, and render something plausible, not merely serve as decoration. 

3.4.1

Show more than two dimensions

The simplest and best way to achieve interesting analyses is to show more than two dimensions of a business situation. This concerns primarily the visual processing of data in the form of charts. In a chart with only one dimension (such as in a pie chart), only mundane things are visible which could also be stated easily in a simple sentence. Even charts with two dimensions can yield very interesting relationships – yet those charts with three, four and five dimensions yield structures that can analyze complex situations and lead to interesting and completely new insights.

3.4.2

Show causes

When the assumptions or basic data upon which a business analysis is based are also shown, the results are not only understood better, they are also much more convincing. A typical example of this is key data trees, such as the ROI tree.

3.4.3

Show clusters

With the help of clusters, in two and three dimensional forms, large amounts of data can very often provide interesting and new insights.

3.4.4

Show correlations

When several data series are to be compared, correlations are often sought in order to better understand the interrelations. Suitable rankings and comparisons can serve to support the search for correlations.