Transforms

Transforms allow you to format data so that it can be imported into EngageIP. Transforms can be be as simple as trimming whitespace to more complex cases combining multiple fields and applying a formula before importing into EngageIP. There are two distinct stages at which point a transform can take place: extracting the data from a file and importing into EnageIP. The differences are noted below.

Field Transforms

Field transforms allow you to format the data as it is read from the incoming file. Examples of transforms at this phase of an import are:

TransformDescription
Case ConversionAllows you to convert the file's data to upper, lower, or title
ConditionalPerform conditonal logic based on a comparison
Date ConversionsFormat a date/time
RegexUse regular expressions to format data
SubstituteReplace incoming data
TimeConvert to 24 hour format
TrimRemove white space left or right of the data

Mapping Transforms

Mapping transforms are used to format data before importing as an EngageIP object. Transforms can be applied to single fields or used to combine fields. The results of a transform can also be mapped to a property of an EngageIP object, chained together using another transform, or both at the same time! Thus, it is possible to map many input fields into a single field in EngageIP or map a single input field into many EngageIP fields.

TransformDescription
CombineCombines multiple input fields into a single string with formatting
FormulaApply a formula to a input value or combination of input values
LiteralDefault the value of the EngageIP property
MapUses a data map to import file values to values that are valid in EngageIP
Map to IDUses a data map to import file values to an ID in EngageIP
MatchFinds the EngageIP ID by name using the import field value