📘 What You’ll Learn in Session Four Link to

1) The purpose and power of DataWeave, MuleSoft’s core transformation language

• When and how to use key DataWeave functions: map, filter, reduce, groupBy, orderBy, ++, and default

• The structure of a DataWeave script (header, delimiter, body) and how to avoid common syntax errors

• How to identify and handle data types (arrays, objects, strings, numbers, nulls) to prevent transformation errors

• Real-world and exam-style transformation examples, including:

• Concatenating name fields

• Mapping arrays of objects

• Filtering for active entries

• Reducing values for totals

• Grouping and sorting by fields

• Default values for missing data

• Joining related data using map + filter

• How to write and read lambda expressions in map, filter, and reduce

• Why function order matters (groupBy vs. orderBy) and how structure affects logic

• How to format output for both humans and systems, including dates and fallback values

2) The complete breakdown of Batch Jobs in MuleSoft:

• What they are, why they matter, and how they work

• Configuration of batch scopes, block sizes, concurrency, and scheduling

• Using acceptExpression and acceptPolicy to control record flow

• When and how to use Batch Aggregators for grouped processing

• What happens in the On Complete phase—and what doesn’t

• Understanding variable scope across batch steps and flow

• Practice flows showing real MuleSoft logger behavior at each stage

  Summary Document:

  https://docs.google.com/document/d/1rHgI77-bB2whyqp1NDZwGYvq-U7bkU9QbemZZj7n1wM/edit?tab=t.0#heading=h.tys6np99t07k