Data Connectors: Transforms (Summer '21 Release)

Product/Library Releases & New Features Summer '21 Release
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With this release we are introducing Transforms to Data Connectors.

Transforms allow you to manipulate incoming data in the Connectors workflow, eliminating the need to perform these actions before the data enters Yext. After choosing a transform action in the Connector workflow, you can preview the changes in real time. Additionally, you can add as many transforms as you’d like.

The following transforms are available:

  • Remove Unwanted Characters
  • Fix Capitalization
  • Filter Rows Based on Criteria
  • Find and Replace
  • Add Column with Static Value
  • Format Dates
  • Pattern Matching/Extraction
  • Plugins

For additional details on each of these transform options, visit the Data Connectors training module.

To add a transform click Transform in the sidebar and select the desired transform. Then you will select which columns you want to apply the transform to. Then select from the support options for that transform. For example, in the screenshot below we have chosen the ‘Fix Capitalization’ transform for 6 columns, and we are applying the ‘All Caps’ option.

1600×861 164 KB

Once you click Apply, the data table preview on the right side will update accordingly based on the select transforms. Once you have applied your transform you can add additional transforms as it’s relevant.

Custom Transforms — Functions
Functions allow users to create fully customized Transforms written as a TypeScript function.

After creating a custom transform, you can then select the plugin in the UI as you would select a built-in transform.

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Hi,
Where and how do I create a custom typescript functions?

Thanks,
Nobu

1 Like
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Even I have the same question as @NOBUYUKI_MITSUTAKE. How can we create and use custom typescript functions?

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Hi Nobu and Yash,

To learn more about Functions, check out our Get Started with Yext Functions guide.

This will walk you through the creation process, and Step 4 outlines what you need in order to write a Function that can be used as a Transform in Data Connectors