Transforms
- Tim Neil
Transforms allow you to format data so that it can be imported into LogiSense Billing. Transforms can be be as simple as trimming whitespace to more complex cases combining multiple fields and applying a formula before importing into the platform. 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:
Transform | Description |
|---|---|
Case Conversion | Allows you to convert the file's data to upper, lower, or title |
Conditional | Perform conditional logic based on a comparison |
Date Conversions | Format a date/time |
Regex | Use regular expressions to format data |
Substitute | Replace incoming data |
Time | Convert to 24 hour format |
Trim | Remove white space left or right of the data |
Mapping Transforms
Mapping transforms are used to format data before importing as a platform 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 a LogiSense Billing 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 the platform or map a single input field into many LogiSense Billing fields.
Transform | Description |
|---|---|
Combine | Combines multiple input fields into a single string with formatting |
Formula | Apply a formula to a input value or combination of input values |
Literal | Default the value of the LogiSense Billing property |
Map | Uses a data map to import file values to values that are valid in the platform |
Map to ID | Uses a data map to import file values to an ID in LogiSense Billing |
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