Anypoint Platform Development: DataWeave 2.0 (Mule 4)

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Course Details

Anypoint Platform Development: DataWeave 2.0 (Mule 4)

Duration: 2 Days 

Course Code: APDD4

Prerequisite:

•    Experience developing Mule 4 applications as demonstrated by one of the following:
o    Passing the MuleSoft Certified Developer - Level 1 (Mule 4) exam
o    Completion of the Anypoint Platform Development: Fundamentals (Mule 4) course
o    Completion of the Anypoint Platform Development: Mule 4 for Mule 3 Users course

•    A basic knowledge of functional programming

Course Description:

This course is for developers interested in advancing their DataWeave 2.0 skills beyond those taught in the Anypoint Platform Development - Fundamentals (Mule 4) course.

Course Objectives:

At the end of this course, students should be able to: 

•    Write generalized and reusable transformations using variables, functions, DataWeave modules and mappings, and dynamic evaluation components.
•    Build complex transformations from smaller testable steps.
•    Build more robust and testable functions and expressions using strong typing, match operators, error handling, and logging.
•    Create, transform, filter, combine, shuffle, select from, and reduce complex data structures that include nested arrays, objects, and arrays of objects.
•    Recursively replace or format every element or a list of elements in a nested schema.

Course Outline:

Module 1: Transforming data using metadata
•    Apply DataWeave fundamentals as learned in the Development Fundamentals course
•    Configure metadata for DataWeave transformation input and output
•    Set example input for DataWeave transformations

Module 2: Organizing DataWeave code with variables and functions
•    Organize DataWeave code into variables and functions
•    Pass functions and lambda expressions as parameters to other DataWeave functions
•    Chain DataWeave functions together
•    Create and use reusable DataWeave modules
•    Write more robust functions using the match operator to test for data types

Module 3: Constructing arrays and objects
•    Add components to and remove elements from arrays and objects
•    Construct objects from lists of DataWeave expressions using object constructor curly braces { }
•    Troubleshoot common issues when using object constructor curly braces { }

Module 4: Iteratively transforming data using mapping operators
•    Transform elements of arrays into a new array using the map operator
•    Transform elements of objects into a new object using the mapObject operator
•    Combine map and mapObject operators to transform complex schema
•    Extract an array of keys and/or values from an object using the pluck operator
•    Reduce and accumulate array elements to other output types using the reduce operator

Module 5: Recursively transforming complex structures
•    Write recursive functions to transform complex schema
•    Replace keys or values at any level of a nested data structure using a lookup object