# Data Transformation
While **Data Mapping** focuses on linking inbound and outbound parameters between components, **Data Transformation** extends this concept by allowing **data to be transformed during the mapping process**.
In ONEWEB, data transformation can be applied **directly on the mapping connection**, enabling developers to modify values, apply formulas, or construct expressions before data is passed to the target component.
***
### Data Transformation vs Data Mapping
| Aspect | Data Mapping | Data Transformation |
| ----------- | --------------------- | ------------------------------------ |
| Purpose | Connect parameters | Modify data during mapping |
| Logic | Direct value transfer | Formula‑based conversion |
| UI | Drag & drop mapping | Formula Editor |
| Typical Use | Pass values as‑is | Calculate, format, or combine values |
Data Transformation is therefore used when values **cannot be passed directly** and must be adjusted to fit the target contract.
***
### Accessing the Formula Editor
To apply data transformation:
1. Create a mapping between two parameters
2. **Double‑click the blue mapping line** connecting the source and target parameters
3. The **Formula Editor panel** opens
This editor allows transformation logic to be defined visually.
***
### Formula Editor Capabilities
The **Formula Editor** allows users to construct transformation expressions by:
* Dragging **process parameters** into the editor
* Using **mathematical operators**
* Applying **String functions**
* Combining multiple inputs into a single output expression
The Formula Editor is available **only in the mapping screen**, ensuring that transformation logic remains closely tied to data flow.
***
### Common Data Transformation Scenarios
Data Transformation is commonly used for:
* Formatting strings (for example, concatenation or trimming)
* Applying arithmetic calculations
* Building composite values from multiple parameters
* Converting data shapes between systems
* Normalizing values before persistence or service calls
These transformations allow systems with different data contracts to interoperate cleanly.
***
### Best Practices for Data Transformation
To maintain clarity and reliability:
* Keep transformation logic **simple and readable**
* Avoid embedding complex business logic in formulas
* Use Microflow or Java Node for advanced transformations
* Clearly name parameters to reflect transformed meaning
* Validate transformation outputs during testing
Well‑designed transformations improve integration robustness and reduce runtime errors.
***
### Summary
**Data Transformation** in ONEWEB allows developers to modify data values during parameter mapping using a visual, formula‑based approach.
With Data Transformation, applications can:
* Apply calculations and string operations inline
* Adapt data between different system contracts
* Keep transformation logic close to data flow
* Avoid unnecessary custom code for simple conversions
Together with **Data Mapping**, Data Transformation completes ONEWEB’s visual integration model, enabling **flexible, readable, and maintainable data flow across systems**.
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