• reveals patterns and trends in the data
• summarizes the data
• reveals interesting phenomena in the data (unexpected rules)
• points out unexpected cases for auditing purposes
• issues predictions for new cases

WizWhy determines how the values of one field in the data are affected by the values of other fields. The system performs its analysis based on one field selected by the user as the dependent variable, while the other fields are the independent variables (or conditions). The dependent variable can be analyzed as either Boolean or continuous.

The user can fine-tune the analysis by defining parameters such as the minimum probability of the rules, the minimum number of cases in each rule and the cost of a miss vs. the cost of false alarm.

WizWhy reveals and lists the rules that relate between the dependent variable and other fields (conditions).  The rules are formulated as if-then and if-and-only-if statements. On the basis of the discovered rules WizWhy points out the main patterns, the unexpected rules (interesting phenomena) and the unexpected cases in the data.

WizWhy can issue predictions for new cases on the basis of the discovered rules. The data of the new cases to be predicted may be entered either manually or read through a given file.

WizWhy calculates the value of the prediction, its conclusive probability and the significance level.  These figures indicate the extent to which the ‘Subject to Predict’ can be relied on. The predictions can be either Boolean or continuous.

WizWhy reads all popular databases either directly or through ODBC or OLE DB. The data may combine two or more jointed tables.