The complete collection of Deep Dives, practical tutorials, Quick Reads and engineering notes across Salesforce, MuleSoft, DataWeave, integration, APIs, distributed systems, testing and developer tooling.
Looking specifically for longer-form architecture and production engineering? Explore the 15 curated Deep Dives →
Practical DataWeave patterns for Salesforce integrations: contract mapping, null handling, field normalization, reusable functions, and keeping transformations maintainable.
Read article →Use DataWeave's default keyword to keep common null and missing-value transformations readable, while knowing when explicit conditions are still the better choice.
Read article →Practical DataWeave filter examples for selecting records, handling optional values, combining conditions, and keeping filtering separate from transformation logic.
Read article →Practical DataWeave patterns for flattening nested arrays, combining parent and child data, and deciding when flatMap is clearer than map followed by flatten.
Read article →Use DataWeave groupBy to turn flat arrays into useful business groupings for aggregation, routing and downstream request construction.
Read article →Learn how DataWeave groupBy turns an array into grouped collections for batching, aggregation, routing, and downstream integration processing.
Read article →A quick, practical guide to choosing map or mapObject in DataWeave, with examples for arrays, objects, keys, values, and common transformation mistakes.
Read article →Use map when transforming array elements and mapObject when transforming object entries. The desired output shape usually makes the choice obvious.
Read article →Understand DataWeave reduce through practical examples for totals, object construction, grouping-like transformations, and choosing the right accumulator.
Read article →Practical DataWeave patterns for omitting null fields from JSON and deciding whether empty strings, arrays, and objects should also be removed.
Read article →A practical guide to when DataWeave streaming helps, what sequential access means, and which transformation patterns can accidentally defeat the memory benefit.
Read article →Learn how to iterate over Map entries in Mule 4 by combining the For Each scope with DataWeave's entrySet function.
Read article →A practical example of combining DataWeave with a Java date-time utility to calculate the last Monday of the previous month in Mule 3.x and Mule 4.x.
Read article →A concise Mule 4/DataWeave troubleshooting note on expressing a not-contains condition when direct negation attempts did not behave as expected.
Read article →An introduction to DataWeave transformation concepts, structure, and a practical JSON-to-Java-to-XML mapping example in MuleSoft.
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