Date/time transformation

A date/time node is used to change timestamp data from one node before it goes into the next node. Date/time transformation is useful when automating time-sensitive processes, analyzing time-based data, and ensuring consistency in date/time representations in your cloud environment. For example, if you want to schedule a backup to run 7 days after a previous one, filter log entries within a specific time window by subtracting the start time from the end time, or convert date/time formats to match the requirements of different APIs.

Note that:

• The date/time node only accepts timestamp data type fields as input from earlier nodes in a CloudFlow.

• The date/time node supports input from both a preceding trigger node or other activity nodes in a CloudFlow.

• Date/time nodes can be chained together.

• Select which field you want to transform: Specifies the field to be transformed. The field must be a timestamp data type field.

• Define the transform action: Defines the action to take for the transformation and saves the output to a new field. Below are the supported transformation operations. Note that different transform actions are configured differently.

  • Add: Adds time to a referenced timestamp field.
  • Subtract: Subtracts time from a referenced timestamp field.
  • Format: Changes a referenced timestamp field to a new format. For example, you might change a date from YYYY-MM-DD to MM/DD/YYYY.

• + Add another transform: Transforms multiple date/time fields simultaneously, applying the same or a different transformation to each one. This is useful for ensuring date fields, such as a start date and end date, are consistently formatted before being used in an API call or downstream process that has strict format requirements.