Compare TrueChem vs. WizWhy

Graphs are generated automatically as a result of data input, eliminating the need for any further steps to produce them. Each component can be visualized according to the default configurations established in System Setup, or users have the flexibility to create a personalized display for each element. Those with the appropriate permissions can access the graphical data and engage in tasks such as approving Corrective Actions and adding Notes. Within the DOCS section, users have the capability to attach various documents including procedures, work instructions, MSDS sheets, videos, photos, or any other necessary documentation. Essentially, if it can be displayed on your computer, TrueChem can showcase it as well. This feature ensures that essential information is readily available when needed the most. Additionally, the system provides Rules and Rule Sets, enabling users to establish “If-Then” scenarios that monitor specific conditions and trigger corresponding actions automatically when those conditions are met. For instance, the configuration can be set to generate a pop-up notification, dispatch an email, or execute other functions based on user-defined criteria, enhancing user interactivity and responsiveness. Overall, this functionality significantly improves the efficiency of managing data and documentation.

WizWhy analyzes how the values of one data field are influenced by the values of other fields in the dataset. The analysis hinges on a dependent variable chosen by the user, while the remaining fields act as independent variables or conditions. This dependent variable can be examined in two ways: as a Boolean value or as a continuous measurement. Users have the ability to refine their analysis by setting various parameters, including the minimum probability for rule formation, the least number of instances required for each rule, and the comparative costs associated with false negatives versus false positives. WizWhy identifies and presents a series of rules that connect the dependent variable with other fields, expressing these rules using if-then and if-and-only-if constructs. Based on the identified rules, WizWhy highlights significant patterns, reveals unexpected rules that may indicate interesting phenomena, and points out unusual cases within the dataset. Additionally, WizWhy is capable of making predictions for new instances by leveraging the established rules.