When building DataWeave transformations for your Mule application, you will run into situations in which you will need to invoke external logic that may be encapsulated in a Java POJO, Groovy, Python, Ruby script, or really any lookup that uses a CSV file or database table as part of the transformation.
When integration involves different applications, systems, or databases, we face a common challenge: how do we bridge between data formats and how can we provide interoperability for fields that store dates and date/time values?
Logic handling using DataWeave is essential for simple mediums and highly complex transformations, in which the mapping requirements necessitate generating outputs based on values provided in the input payload.
