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Transforms

Last Updated: May 14, 2020

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

Match

Finds the system ID by name using the import field value