Field Mapping – How to Map a field

MAPPING EXISTING FIELDS Copy Link

We make sure your data flows seamlessly between apps! For that, Wiresk takes care of retrieving data from your integrated source app and sends it to your destination app, it’s called Field Mapping. 

The Field mapping ensures that your data lands in the right place. 

In most cases, Wiresk will create the mapping for you based on common field names. However, you can personalize your field mapping as you see fit: 

1. Simply click on the field you want to map in your destination app. 

2. Choose your mapping method: 

Flow Input Copy Link

Click on the input field, here you can select preloaded data from your Trigger or your Previous Method. 

You can Map the “Input “field, by just following the branch of the metadata as in the table below, and select the last metadata name, for example: Data > customer > first_name (select “ first_name “if you want to map this metadata) 

Example of field mapping table:  

Example: Mapping the email received date to a Spreadsheet.

• Click on “Input” field, a screen pops up, in the list of Input tab (dataset from the Trigger), select “Date” to Map the email received date in header 1.

Select a default value Copy Link

If the data is pre-defined, like a status or category, you can choose from a list of options displayed dynamically.

Manually Enter a Value Copy Link

Need to set a specific value for the field? You can enter it directly in the manual input field by clicking on the lightning bolt icon, or couple it with a flow input (preloaded data from previous steps) by typing “@”. In the list that appeared, just select the wanted data field to map.

MAPPING ARRAYS Copy Link

Explanation of “⊕ Element” and “⊕ Map” Buttons:

(+) Element Copy Link

This button allows you to manually add a single element to an array.

When mapping data, arrays often contain multiple elements (e.g., multiple invoices, invoice lines, or items in an order). However, if you need to add just one specific element manually instead of mapping a dynamic array, you can use the “+Element” button to do so.

This is useful when:

• You need to insert a fixed value into an array.
• The array should always contain at least one predefined item.
• You are manually configuring an array without relying on dynamic data input.

(+) Map Copy Link

This button is used when you have an array in the input data, and you need to generate one corresponding output element for each item in the array.

This allows Wiresk to dynamically iterate over the input array and create structured output data, regardless of whether the array contains one, ten, or a thousand elements.

When to use it:

• When dealing with complex data structures, such as groups of modifiers, options, or add-ons, where each group contains multiple attributes (e.g., name, type…).
• It allows you to map a collection or group of related fields in a structured manner.

Example: mapping option prices from an array:

• Click on the button and select the option_prices array in the input data.
• For every option price element in the input array, one corresponding output element is created.
• Each field (external_key, name, price, active, default) can be mapped manually or dynamically from the array.

MAPPING WITHIN A STRUCTURED DATASET Copy Link

You can manually Map a field with an Object key-value, with this method, you can specify the order of the Object in an Array from the current step or previous steps.

Mapping from the current step: Copy Link

Requires you to Map an array field first, refer to (+) Map.

1 – Input manually with the lightning bold icon (refer to the step above):

{{local.0.fieldName }}

• The local keyword refer to the Mapped dataset within the current step.
• The 0 represents the depth level of the locally mapped data structure.
• The fieldName represents a specific field within the indexed array object.

Suppose you receive an object with the following structure:

firstname  
lastname  
invoices (array of invoices)  
   ├── invoice_date  
   ├── amount  
   ├── invoice_lines (array of line items)  
       ├── productid  
       ├── name  

If you map the invoices array in a step, you’ll be working with an object that contains invoice_date, amount, and another array (invoice_lines).

• To access invoice_date within the invoice mapping, you use: local.0.invoice_date This means “invoice_date from the first level of mapped array (invoices)”.
• Now, inside the mapping of invoice_lines, you’re at a deeper level (inside invoice_lines which is an array inside invoices).
  • To access productid inside invoice_lines, you use: local.1.productid
  • Here, local.1 refers to the second level of array mapping (invoice_lines).

2 – You will need to set each mapped field Calculation type as a String Interpolation.

• Select the Ellipsis icon (…)
• Select String Interpolation

Mapping from previous steps: Copy Link

Enter manually via the Lightning bold icon:

{{context_data.stepx.x.fieldName}} or {{context_data.stepx.fieldName}}

where:

• context_data → The top-level object containing workflow-related data.
• stepx → Represents a specific step in your Flow, where x is the placeholder for the step. 0 is the first step in your Flow, 1 is the second etc…
• x (represent a number after stepx) indicates the numerical order within the array. 0 represent the first object, 1 the second etc…
• fieldName → The specific field within the object that needs to be mapped.

Don’t forget to set each mapped field Calculation type as a String Interpolation.

Don’t stop here! Copy Link