Build Custom Transformation

The Custom Transformation empowers users to create custom workflows by assembling transformation steps in a modular and flexible way. It offers complete control over data transformation processes, enabling users to design their own “recipe” of steps tailored to their needs.

How Does It Work?

1. 1Create a Blank Template‍
   Start by creating an empty transformation template.

Note

Now you can start building custom transformation directly from the Recipe Templates page.

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2. 2‍Add and Manage Steps‍
   Build your transformation process by adding any combination of steps:‍
1. Blend Data
2. Filter Data
3. Join Data
4. Group Data
5. Prompt‍
   

Note

You can easily add, rename, or remove steps in an existing recipe at any time. Extend your current logic with additional filters, joins, data sources, and mappings without rebuilding workflows from scratch.

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3. 3‍Add Data to Step
   Fill in the step with the content and logic you wan to apply.

4. 4‍Run and Save
   Once the step is configured, execute the transformation and save the workflow.

5. 5‍Add New Steps
   Continue refining the workflow by adding more steps as needed. You can always revisit existing steps to adjust or improve them.

Use Case

Combining and Joining Data with Blend and Join Steps

Let’s consider an example of combining data from multiple sources and performing a join operation.

Goal

Create a unified dataset that blends Facebook and Google Ads data, then joins Google Analytics 4 (GA4) metrics with Paid Ads data.

‍Steps

1. 1‍Create a Blank Template: Start a blank transformation and name it “Paid Ads and Google Analytics”. Set the target table name as “paid_ads_google_analytics_ai”.
2. 2Add Blend Data Step:
1. Add columns you would like to have in the recipe.
2. Add sources you would like to blend together.
3. Use AI Autofill to find the right mapping quickly.
4. Click Run and Save to update the table.
3. 3‍Add Join Data Step:
1. Add a new step and configure the Join Data operation.
2. Select Google Analytics 4 as the table to join with Paid Ads data.
3. Use AI Autofill to find the correct way to join data.
4. Click Run and Save to update the table.

Conclusion

The Custom Transformation offers unparalleled flexibility in designing data workflows. It streamlines even the most complex data processes by enabling users to create, customize, and expand workflows with modular steps. Whether blending cross-channel data, performing advanced joins, or layering transformations step-by-step, this tool ensures your data is prepared, actionable, and ready for analysis.