Anypoint Platform Development: DataWeave 2.0 (Mule 4) Course Overview

Anypoint Platform Development: DataWeave 2.0 (Mule 4) Course Overview

The Anypoint Platform Development: DataWeave 2.0 (Mule 4) course is designed to enhance the skills of developers who have foundational knowledge in MuleSoft's Anypoint Platform and seek to master data transformation with DataWeave 2.0. This course delves into advanced DataWeave concepts, enabling learners to effectively transform and manage data with precision and ease.

Through various modules, participants will learn to apply DataWeave fundamentals to transform data using metadata, organize code with variables and functions, and construct complex arrays and objects. They will also master iterative transformations with mapping operators and tackle challenging scenarios involving recursive transformations of complex structures.

Upon completing this course, developers will be equipped with the expertise to create sophisticated data transformations, leading to more efficient data integration and application development within the MuleSoft ecosystem. This knowledge is critical for those looking to excel in roles that require advanced data manipulation and integration capabilities.

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

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  • Live Online Training (Duration : 16 Hours)
  • Per Participant

♱ Excluding VAT/GST

Classroom Training price is on request

You can request classroom training in any city on any date by Requesting More Information

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Course Prerequisites

Certainly! Here are the minimum required prerequisites for successfully undertaking training in the Anypoint Platform Development: DataWeave 2.0 (Mule 4) course, formatted for the FAQ section:


  • Basic understanding of data structures (like JSON, XML, and CSV) and their manipulation.
  • Fundamental knowledge of programming concepts such as variables, loops, conditionals, and functions.
  • Completion of the Anypoint Platform Development - Fundamentals (Mule 4) course or equivalent practical experience with MuleSoft's Anypoint Platform and Mule runtime.
  • Familiarity with Mule 4 applications and the MuleSoft development environment.
  • An understanding of the core concepts of MuleSoft's DataWeave language, including using selectors, functions, and directives.

These prerequisites ensure that you have a solid foundation upon which the DataWeave 2.0 training will build, allowing you to fully benefit from the course content.


Target Audience for Anypoint Platform Development: DataWeave 2.0 (Mule 4)

The Anypoint Platform Development: DataWeave 2.0 (Mule 4) course is designed for IT professionals seeking to master data transformation in MuleSoft's Anypoint Platform.


Target audience for the course includes:


  • MuleSoft Developers
  • Data Integration Specialists
  • Software Engineers focusing on Integration Solutions
  • API Developers
  • Systems Architects
  • IT Professionals working with ETL tools
  • Technical Leads overseeing integration projects
  • DevOps Engineers involved in Continuous Integration/Continuous Deployment (CI/CD) processes for Mule applications
  • Data Analysts needing to manipulate and transform data within Mule flows
  • IT Consultants specializing in enterprise integration solutions
  • Technical Project Managers responsible for delivering MuleSoft integration projects


Learning Objectives - What you will Learn in this Anypoint Platform Development: DataWeave 2.0 (Mule 4)?

Introduction to Learning Outcomes and Concepts

In the Anypoint Platform Development: DataWeave 2.0 (Mule 4) course, learners will master advanced data transformation techniques using DataWeave, enhancing their MuleSoft development skills to handle complex data integration challenges.

Learning Objectives and Outcomes

  • Understand and apply DataWeave fundamentals for data transformation, building upon skills acquired in the Development Fundamentals course.
  • Configure and utilize metadata effectively to inform DataWeave transformations, ensuring accurate input and output data structures.
  • Create and manage example input data for DataWeave scripts, facilitating testing and validation of transformations.
  • Organize DataWeave scripts efficiently using variables and functions, promoting code reusability and maintainability.
  • Implement functions and lambda expressions, passing them as parameters to enhance the modularity of DataWeave code.
  • Chain multiple DataWeave functions together to perform complex data manipulation tasks.
  • Develop and incorporate reusable DataWeave modules, streamlining the development process across multiple integration projects.
  • Utilize the match operator to write robust functions that handle different data types and patterns effectively.
  • Manipulate arrays and objects, adding or removing elements, and constructing dynamic objects using DataWeave expressions.
  • Apply mapping operators such as map, mapObject, and pluck to iteratively transform data, and use the reduce operator to process and accumulate array elements.
  • Write recursive functions to process complex and nested data structures, and manipulate data at any level using lookup objects.