Anypoint Platform Development: DataWeave 1.0 (Mule 3) Course Overview

Anypoint Platform Development: DataWeave 1.0 (Mule 3) Course Overview

The "Anypoint Platform Development: DataWeave 1.0 (Mule 3)" course is designed to help learners master data transformation using DataWeave 1.0, a powerful language native to MuleSoft's Anypoint Platform. Through the course's structured modules, students will review DataWeave fundamentals, understand how to match DataWeave types and conditions, and learn to organize and reuse code effectively using variables and functions. This training is essential for developers working on data integration and transformation tasks in Mule 3 applications.

As learners progress, they will delve into array and object construction, including adding and removing elements, utilizing object constructor curly braces, and joining data with map operators. Iteratively transforming data using mapping operators will be covered, equipping students with the skills to transform data structures efficiently. The course culminates with lessons on writing recursive functions and employing match operators to transform complex schemas, ensuring a comprehensive understanding of DataWeave's capabilities for real-world data integration challenges.

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  • Live Online Training (Duration : 8 Hours)
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  • Live Online Training (Duration : 8 Hours)
  • Per Participant

♱ Excluding VAT/GST

Classroom Training price is on request

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Course Prerequisites

To ensure a successful learning experience in the Anypoint Platform Development: DataWeave 1.0 (Mule 3) course, participants should have the following minimum required knowledge:


  • Basic understanding of data structures such as JSON, XML, and CSV
  • Familiarity with the fundamentals of programming (variables, functions, loops)
  • Some exposure to or experience with Mule 3 and Mule Expression Language (MEL)
  • An understanding of core Mule concepts, such as flows, connectors, and transformations
  • Basic problem-solving skills and the ability to troubleshoot simple code errors

Participants are not expected to be experts in these areas, but a foundational knowledge will help them grasp the course material more effectively. This course is designed to build upon these basics and introduce more advanced DataWeave coding techniques and best practices.


Target Audience for Anypoint Platform Development: DataWeave 1.0 (Mule 3)

Anypoint Platform Development: DataWeave 1.0 (Mule 3) is a specialized course aimed at professionals looking to master data integration and transformation.


  • Software Developers and Engineers with a focus on data integration
  • IT Professionals working with MuleSoft's Anypoint Platform
  • Data Analysts who need to manipulate and transform data
  • Integration Architects designing complex data processing flows
  • ETL Specialists looking to leverage DataWeave in their data transformation tasks
  • Systems Administrators responsible for maintaining Mule applications
  • Technical Project Managers overseeing integration projects
  • MuleSoft Consultants and Partners needing in-depth DataWeave knowledge
  • DevOps Engineers involved in continuous integration and deployment of Mule applications
  • Business Analysts requiring an understanding of data transformation logic for better system design


Learning Objectives - What you will Learn in this Anypoint Platform Development: DataWeave 1.0 (Mule 3)?

Introduction to the Course's Learning Outcomes and Concepts Covered

Gain in-depth knowledge on DataWeave 1.0 in Mule 3, mastering data transformation, reusability, construction of complex types, and recursive processing in Anypoint Platform Development.

Learning Objectives and Outcomes

  • Understand the fundamentals of DataWeave language and syntax used in Mule 3 applications.
  • Identify and apply appropriate DataWeave types and conditional logic to process data.
  • Organize code effectively using variables and functions for better reusability and readability.
  • Manipulate arrays and objects, including adding and removing elements, and constructing objects using DataWeave expressions.
  • Resolve common issues associated with object constructor curly braces in DataWeave.
  • Employ map operators to join and transform data from various sources into unified arrays or objects.
  • Utilize the map operator to transform array elements into a new array with the desired structure.
  • Apply the mapObject operator to convert object elements into a new object, maintaining or changing the schema as required.
  • Integrate map and mapObject operators to handle and transform complex data schemas iteratively.
  • Develop recursive functions to process and transform deeply nested and complex data structures effectively.