Transformation Step

The Transformation step in RiskOS™ lets you manipulate data within a workflow using a set of predefined, stateless functions. Transformations do not maintain state; they operate only on the data provided as inputs at the time of execution.

For example, you can use the CONCAT function to combine firstName and surName into a single fullName variable. That new variable becomes immediately available to downstream steps, simplifying logic and reducing duplication.

How transformations work

Each transformation is a predefined, stateless operation: given the same inputs, it always produces the same output, and it keeps no memory between runs. A Transformation step has three parts:

• Inputs — You supply each input as either a Value (a static string or number) or a Variable (a payload field or the output of an earlier step). The step passes inputs to the function in the order listed for that function, so order matters.
• Output — The function returns a single typed value: a string, number, Boolean, array, or — for pass-through functions such as COPY — any type. RiskOS™ stores that value in the output field you name, which downstream steps reference as $outputFieldName.
• Type handling — In general, if an input is missing or is not the type a function expects, the function returns a safe default rather than failing the workflow: string functions return an empty string, numeric functions return 0, and Boolean functions return false.

Placement in a workflow

• A Transformation step can be placed anywhere in a workflow, depending on your logic.
• Common patterns include:
  • Right after the Input step to normalize incoming data.
  • Before a Condition step to prepare data for evaluation.
  • After an Enrichment step to parse out specific data.

flowchart LR
    A[Input] --> B[Transformation: normalize data]
    B --> C[Condition] --> D[Decision]

Configure a Transformation step

1. Add the Transformation step to your workflow, then click the step to open the side panel.

2. Select a Function from the dropdown (see the Available functions section).

3. Provide input parameters for the function:
   • Value: For static values (e.g., strings, numbers).
   • Variable: For dynamic inputs, such as payload fields or outputs from prior steps.
4. Specify the output field name.
   • The function’s result is stored in this field.
   • Use it later with $[output_field_name].
   • Example: If you name the output field fullName, reference it downstream as $fullName.

Available functions

Each row lists a function's inputs, output type, how it works, and a worked example (shown as inputs → output).

String functions

Numerical functions

Array functions

Date functions

Date functions expect ISO 8601 dates (YYYY-MM-DD). A compact YYYYMMDD value such as "19900615" is not a valid ISO date, so CALCULATE_AGE cannot parse it and does not return a valid age. To convert a YYYYMMDD value inside the workflow, split it with SUBSTRING and rejoin it with CONCAT before calling CALCULATE_AGE: SUBSTRING($dob, 0, 4), SUBSTRING($dob, 4, 6), and SUBSTRING($dob, 6, 8) return the year, month, and day, then CONCAT($year, "-", $month, "-", $day) produces "1990-06-15".

Special functions

Best practices

• Place transformations where they add clarity or efficiency — e.g., normalize data early, simplify condition checks, or prep values before decisions.
• Use clear names for output fields so they’re self-explanatory in downstream steps.
• Validate transformation results with test payloads to avoid logic errors.