In this chapter we have covered different ways to represent our knowledge in Drools.

For a tailored language for specific use cases, DSL/DSLR could be a solution that hides the complexity of the DRL syntax behind a language that is more familiar to an SME.

For situations where a big set of rules with a common structure is required, decision tables could be a perfect fit. The big advantage of decision tables is that they are very concise and user-friendly.

When more flexibility in the structure of the rules is required, rule templates could be a good help. The out of the box support for data sources such as spreadsheets, objects, or even a SQL store makes rule templates a very interesting option.

If we are dealing with non-rule based knowledge such as neural networks, decision trees, or scorecards, we must consider the use of the drools-pmml module. Maybe this is not the best performance solution but it allows us to easily integrate these models with our current rule-based solution.

Now that we have a better understanding about the DRL language and the more human-friendly alternatives that we can use to express our knowledge bases, it is time to understand the best practices regarding how rules can be tested in Drools and how to detect and troubleshoot our KIE Bases and KIE Sessions. The next chapter is all about this topic.