What format does DataWeave typically use to define transformations?

DataWeave, the data transformation language used in MuleSoft, primarily utilizes a functional programming style syntax for defining transformations. This approach emphasizes the use of functions to manipulate data, making it easier to express complex transformations in a concise manner. In functional programming, functions are first-class citizens, allowing for operations such as mapping, filtering, and reducing data sets without altering the underlying data structures.

By employing a functional programming syntax, DataWeave enables developers to focus on the transformations themselves rather than the control flow, which enhances code readability and maintainability. This design choice aligns well with data manipulation needs, presenting a powerful toolkit for data transformation tasks effectively.

The other formats mentioned, such as procedural or object-oriented programming styles, would emphasize different paradigms of coding that are not as straightforward for transformation purposes. Additionally, a markup language syntax focuses more on structuring or describing data rather than transforming it, which is not the primary goal of DataWeave. Thus, recognizing the functional programming style as the correct approach emphasizes the advantages it brings to the transformation process.