Configure Data Transformation

Configure Data Transformation

Data Transformation changes the selected resulting target-field value after any applicable Advanced Data Mapping and Advanced Database Mapping stages. Define each supported transformation from the available field references and operators, then verify normal, empty, boundary, and exception outputs.

Transformation changes the resulting value

Mapping determines where a supported value is written. Data Transformation changes the resulting selected target-field value. Review the final destination before approving the transformation.

Before you start

Prepare:

• the selected data type and resulting target field;
• the field reference or value used by the transformation;
• the required supported operator or expression;
• the source value type and required target field type;
• normal, empty, invalid, and edge-case examples;
• the exact expected output.

Transformation controls

Each transformation can include:

Control	Purpose
Target Field	Selects the resulting target field whose value will be produced or changed.
Value type indicator	Shows the expected field representation, such as text or number.
Operator	Selects a supported transformation operator.
Field Reference	Inserts a supported field reference into the expression.
Expression area	Displays or accepts the transformation expression.
Add Rule	Adds another transformation for the selected or another data type.
Delete	Removes the transformation rule.

Available operators and field references depend on the migration path and supported data model.

Configure a transformation

1. Open Data Transformation

   In Add-ons, expand Data Transformation.

2. Select the data type and resulting target field

   Confirm that the selected field is the destination that should contain the transformed result after applicable mapping stages.

3. Select the operator

   Choose a supported transformation operator that represents the approved value change.

4. Insert the required field reference

   Select the supported field used to calculate or build the target value.

5. Complete the expression

   Enter or review the expression that produces the required output.

6. Test normal and edge cases

   Check representative values, empty values, long text, negative or decimal numbers, and unexpected source formats where relevant.

7. Add other required transformations

   Keep each rule focused on one defined output and remove conflicting rules.

Practical use cases

Use Data Transformation when the target destination is already known and the resulting value itself must change through a supported rule.

Requirement	Data Transformation role	What to verify
Increase the resulting Product Regular Price by an approved 12%	Apply the supported arithmetic rule to the known resulting target field after any applicable mapping stages.	Normal prices, decimals, empty values, and business-specific boundaries produce the approved final price.
Normalize a supported numeric result to an agreed precision	Apply a supported rounding or numeric-normalization expression to the selected resulting target field.	Values immediately above and below rounding boundaries remain correct and the change does not introduce unintended totals or precision loss.

Review transformation risks

Value or field role	What to confirm
Identifier	The transformation does not create duplicate or unmatchable identifiers.
Numeric value	Rounding, precision, minimums, maximums, and currency behavior are approved.
Text value	Length, encoding, capitalization, and empty-value behavior are valid.
Boolean or status value	The result matches target-supported values and does not replace Attribute Mapping.
Date or time value	Format and time zone behavior are compatible with the Target Platform.
Relationship field	Related records continue to use compatible identifiers.

Do not transform relationship keys without technical validation

Product IDs, Customer IDs, Order IDs, foreign keys, and other relationship-critical values can break links between records when transformed incorrectly.

Interaction with other configuration

The fixed Add-on sequence is:

Data Filter → Advanced Data Mapping → Advanced Database Mapping → Data Transformation

• Data Filter determines whether a record continues to later Add-on stages.
• Attribute Mapping aligns standard operational values such as languages and order states.
• Advanced Data Mapping establishes supported field-level destinations when applicable.
• Advanced Database Mapping establishes eligible supported field or database-column destinations when applicable.
• Data Transformation changes the selected resulting target-field value after the mapping stages.
• Customization handles approved tailored processing outside Standard Add-on scope.

Expected result

After configuring Data Transformation:

• each rule changes the intended resulting target-field value;
• the transformed result uses a target-compatible value type;
• empty and edge-case inputs follow the approved behavior;
• identifiers and relationships remain valid;
• the transformation is evaluated after applicable mapping stages;
• representative records produce the approved final value.

Verify the transformation

Check	Pass condition
Target field	The intended resulting target field is selected.
Value type	The expression produces a value the target field can represent correctly.
Normal example	A representative input produces the expected output.
Empty input	Empty or missing values follow the approved behavior.
Edge cases	Long, negative, decimal, special-character, or boundary values remain valid.
Mapping interaction	The transformation applies to the intended field after applicable mapping stages.
Uniqueness	The transformation does not create duplicate unique values.
Relationships	Relationship-critical values remain linkable.

If this does not work

Issue	What to do
The required operator is unavailable	Use only supported operators or prepare the unsupported portion for Custom Service review.
The field reference is missing	Confirm that the data type and field are supported for the migration path.
The expression returns an incompatible value	Change the rule so the result can be represented by the target field.
Values become empty or malformed	Review source formatting, null handling, and expression syntax.
Unique values collide	Revise or remove the transformation before execution.
The transformation is attached to the wrong destination	Correct the applicable Advanced Data Mapping or Advanced Database Mapping rule first, then retest the transformation.
The requirement needs multi-record, bespoke, or external-system logic	Prepare a Tailored Add-on, Custom Add-on, or broader Custom Service requirement as appropriate.

Next step

Return to Configure Add-ons and review the transformation together with any filters and mapping rules.