MuleSoft Mule4 training| Anypoint Platform Development: DataWeave

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

Write generalized and reusable transformations using variables, functions, and DataWeave modules.
Use the DataWeave Playground to test and author DataWeave code.
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.
Reduce arrays to other data structures or data types and calculate key performance indicators.

Applying DataWeave fundamentals
- Review and apply DataWeave fundamentals as learned in the Anypoint Platform Development: Fundamentals course
- Set example input to preview DataWeave results in Anypoint Studio
- Chain together two argument functions by using infix notation
- Filter, order, and group elements of an object or array
- Retype DataWeave expressions in the middle of code execution
Organizing reusing DataWeave code
- Organize DataWeave code into variables and functions
- Enclose variables and functions in do statement scopes
- Pass functions and lambda expressions as arguments to other DataWeave functions
- Create and use reusable DataWeave modules
Writing more defensive and more robust DataWeave
- Write more defensive DataWeave expressions that filter and route data based upon conditions
- Write more robust functions using a match operator to test for data types
- Handle and raise errors
- Log from inside DataWeave expressions
Constructing arrays and objects
- Add components to and remove elements from arrays and objects
- Construct objects from lists of DataWeave expressions by using object constructor curly braces { }
- Troubleshoot common issues when using object constructor curly braces { }
Iteratively mapping and joining arrays and objects
- Combine objects and arrays into nested data structures by using map and mapObject functions
- Extract an array of keys and/or values from an object by using the pluck function
- Extract an array of keys and/or values from an object by using the DataWeave core Arrays module functions
- Conditionally join together two nested schemas by using the join function
Updating inside nested data structures
- Conditionally update and mask parts of nested data structures
- Format and transform nested data structures by using recursive functions
Reducing data from arrays
- Conditionally test, count, and sum up elements of an array by using the DataWeave core Arrays module
- Reduce and accumulate array elements to other output types by using the reduce function
- Calculate key performance indicators from input collections by using the reduce function

MuleSoft Anypoint Platform Development: DataWeave

DataWeave 2.0 training for developers from official MuleSoft Partners.

We are a trusted MuleSoft partner

Anypoint Platform Development: DataWeave

Objectives

Pre-requisites

Outline

Applying DataWeave fundamentals

Organizing reusing DataWeave code

Writing more defensive and more robust DataWeave

Constructing arrays and objects

Iteratively mapping and joining arrays and objects

Updating inside nested data structures

Reducing data from arrays

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