Flatten JSON Object
Infoveave Data Automation — Pivot & Transpose
JSON strings buried in a single column become clean, named flat columns — no parsing code required.
APIs, webhooks, and modern databases frequently return structured data embedded as JSON strings inside individual columns. When this happens, it is impossible to filter, sort, group, or join on the nested field values without first parsing the JSON and promoting individual properties to their own columns. Flatten JSON Object does exactly that — it reads a JSON object stored as text in a column and adds one new flat column to the dataset per property found in that object, named using the original column name and the property key. The result is a properly flat table where every property that was locked inside a JSON string is now an accessible, filterable, and joinable column.
What Flatten JSON Object does
Flatten JSON object columns into individual flat columns in Infoveave. Extract structured nested properties from JSON strings stored in dataset columns without writing parsing code.
When to use Flatten JSON Object
- A column in your dataset contains JSON object strings returned from an API, webhook, or NoSQL export, and you need to access or filter on individual properties within that JSON
- You are processing API responses or event logs stored in a database where structured metadata is serialized as a JSON string in a column rather than split into individual columns
- You want to join on a property nested inside a JSON column — for example matching on an id or region property stored inside a metadata column
- You are building a structured analytical dataset from semi-structured source data and need to normalize JSON columns into flat columns for BI reporting
When to avoid it
- Your column contains a JSON array rather than a JSON object — use Flatten JSON Array, which expands array elements into rows
- The JSON inside the column is deeply nested with multiple layers of nesting — Flatten JSON Object handles one level at a time, so deeply nested structures require multiple flattening steps or a pre-processing transformation
- You only need to extract one specific property from the JSON — consider using a Calculated Column with a JSON path expression instead of fully flattening all properties
Where it fits in your Infoveave automation
Flatten JSON Object is one step inside a multi-step Infoveave workflow. Chain it with other activities — no code, no manual hand-offs.
Build this workflow visually in Infoveave Data Automation — drag, connect, and schedule with no infrastructure setup.
How teams use Flatten JSON Object
Real scenarios where this transformation saves hours of manual work.
Extract Contact Details from API Metadata Column
A SaaS platform exports customer records where a contact column contains a serialized JSON object with email and phone properties packed into a single cell. Flatten JSON Object reads that column and adds two new columns named contact_email and contact_phone to every dataset row. Downstream steps can then filter, deduplicate, or export those contact properties as standard flat columns without any JSON parsing code.
Normalize Product Attributes from E-Commerce API
An e-commerce team ingests a product feed from a marketplace API where each product row has an attributes column containing a JSON object with color, size, and material properties. Flatten JSON Object expands that column into attributes_color, attributes_size, and attributes_material flat columns. The team can then filter by color, group by size, and build product segmentation reports without needing to write any JSON parsing logic.
Extract Transaction Enrichment Details from Payment Gateway Logs
A financial operations team processes payment gateway logs where each transaction row has an enrichment column containing a JSON object with merchant category code, country, and fraud score returned by the payment processor. Flatten JSON Object extracts those fields into flat columns, allowing the team to filter transactions by merchant category, flag high-risk fraud scores, and aggregate by country without manual parsing.
See Flatten JSON Object in action
Input data (left) is transformed using the configuration below. The output table (right) is ready for dashboards or downstream steps.
contactInput Data
| ID | Name | contact |
|---|---|---|
| 1 | Alice | email: [email protected] | phone: 111-2222 |
| 2 | Bob | email: [email protected] | phone: 333-4444 |
| 3 | Carol | email: [email protected] | phone: 555-6666 |
Output Data
| ID | Name | contact | contact_email | contact_phone |
|---|---|---|---|---|
| 1 | Alice | email: [email protected] | phone: 111-2222 | [email protected] | 111-2222 |
| 2 | Bob | email: [email protected] | phone: 333-4444 | [email protected] | 333-4444 |
| 3 | Carol | email: [email protected] | phone: 555-6666 | [email protected] | 555-6666 |
Configuration
Key fields to configure in the Infoveave workflow builder. Full reference available in the documentation.
Columns
Select one or more columns that contain JSON object strings. Infoveave parses each selected column and adds new flat columns for every property found. All new columns are named using the format originalcolumnname_propertykey — for example flattening a column named contact that has email and phone properties adds contact_email and contact_phone columns to the dataset.
Output column naming
New columns are automatically named as a combination of the source column name underscore the JSON property key. This naming convention makes it easy to trace which column each extracted property came from, and allows multiple JSON columns to be flattened in a single step without column name collisions.
Frequently asked questions
Everything you need to know about Flatten JSON Object in Infoveave.
Also in Pivot & Transpose — and what runs before & after
Transformations in the same family as Flatten JSON Object, often chained together in the same Infoveave workflow.
Part of Infoveave Data Automation
80+ transformations. Zero manual steps.
Flatten JSON Object is one of over 80 transformation activities available inside Infoveave workflows. Chain transformations together — no code, no exports, no waiting for IT.
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