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A new Mule application under development must implement extensive data transformation logic. Some of the data transformation functionality is already available as external transformation services that are mature and widely used across the organization; the rest is highly specific to the new Mule application. The organization follows a rigorous testing approach, where every service and application must be extensively acceptance tested before it is allowed to go into production. What is the best way to implement the data transformation logic for this new Mule application while minimizing the overall testing effort?
Correct Answer: D
Correct answer is Implement transformation logic in the new Mule application using DataWeave, invoking existing transformation services when possible. * The key here minimal testing effort, "Extend existing transformation logic" is not a feasible option because additional functionality is highly specific to the new Mule application so it should not be a part of commonly used functionality. So this option is ruled out. * "Implement transformation logic in the new Mule application using DataWeave, replicating the transformation logic of existing transformation services" Replicating the transformation logic of existing transformation services will cause duplicity of code. So this option is ruled out. * "Implement and expose all transformation logic as microservices using DataWeave, so it can be reused by any application component that needs it, including the new Mule application" as question specifies that the transformation is app specific and wont be used outside