Dealing With Unknown Data

DMCommunity.org published an interesting challenge unknownGreeting a Customer with Unknown Data” that deals with the real-world decision modeling issue: your decision model has to produce a meaningful outcome even when expected input is not available. We provided our DMN-like solution utilizing various OpenRules constructs – it is described here.

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Developing Custom Decision Modeling Languages with Enhanced DMN

The modern Business Rules and Decision Management Systems help users to move business logic from a code to business rules controlled by subject matter experts (not developers).  In particular, the latest Decision Model and Notation (DMN) standard [1] defines powerful and broadly applicable concepts for decision modeling that allowed experts [2] to call DMN a “decision modeling language”. DMN even includes a friendly enough expression language, FEEL, to express complex relationships between different decision variables. However, DMN is a general purpose “decision modeling language” that naturally stays away from domain-specific decision modeling constructs. In this article I will discuss how to enhance DMN to support specialized decision modeling languages. Continue reading