What JSON unflattening is
Rebuild nested structure from path and value pairs
JSON unflattening interprets each top-level key as a path and places its value at the matching location in a nested document. A key such as user.address.city becomes nesteduser, address, and cityobjects without changing the original JSON value.
Relationship to JSON Flattener
Reverse UtilityDock's dot and bracket path output
JSON Flattener turns nested leaves into one-level path/value pairs. JSON Unflattener performs the reverse operation. Select the same notation, review any path conflicts, and compare the reconstructed result when exact round-trip behavior matters.
ETL workflows
Restore API and event payloads after flat-field processing
ETL pipelines often flatten nested fields for mapping, filtering, or warehouse staging. Reconstructing those paths produces application-ready payloads after transformations are complete, while indexed segments restore array structure.
- Rebuild nested API request bodies
- Restore event payloads after field mapping
- Convert flat staging records into application JSON
- Verify round trips during ETL development
- Review conflicting mappings before import
- Create readable fixtures from flat key stores
Configuration management
Turn path-based settings into nested configuration
Configuration tools and environment mapping layers commonly represent nested settings as flat keys. Unflattening converts those keys into a document that can be validated, diffed, and supplied to software expecting nested JSON.
Data migration
Move flat exports into systems with nested document models
During migrations, path columns can describe the destination structure without custom scripts. UtilityDock reconstructs objects and arrays, reports incompatible paths, and leaves the source file on your device.
Analytics pipelines
Reassemble nested records after column-oriented analysis
Flat analytics fields are useful for aggregation, but downstream services may require the original event shape. Unflattening turns dot or bracket keys back into nested event records while retaining booleans, numbers, strings, nulls, empty objects, and empty arrays.
Examples
Use the path convention already present in your data
| Input path | Reconstructed location |
|---|---|
user.address.city | {"user":{"address":{"city":...}}} |
user[address][city] | {"user":{"address":{"city":...}}} |
items[0].name | {"items":[{"name":...}]} |
Data Toolkit
Continue with related UtilityDock JSON workflows
FAQ
Questions about unflattening JSON
Does UtilityDock upload or store my flattened JSON?
No. Your files never leave your computer. Validation, path parsing, reconstruction, preview, copying, and download creation all happen locally inside your browser.
Which path formats can I unflatten?
Version 1 supports dot paths such as user.address.city, bracket paths such as user[address][city], and indexed arrays such as items[0].name or items[0][name].
How are arrays reconstructed?
Numeric path segments are treated as array indexes. UtilityDock creates arrays at those positions and preserves the supplied index order in the resulting JSON.
What is a path conflict?
A conflict occurs when one path defines a value where another path needs an object or array, such as user and user.name. The conflicting path is skipped and reported as a warning.
Can JSON Flattener output be reconstructed here?
Yes. Select the same dot or bracket notation used by JSON Flattener. Escaped separators, indexed arrays, primitives, and empty containers are supported.
Does this tool infer schemas or run custom transformations?
No. It reconstructs structure from supported key paths only. Version 1 does not infer schemas, execute scripts, apply arbitrary rules, or call APIs.