Building fundamentals
Course overview
Pulling data
Transforming data
Exporting data & dashboards
Exporting data &
dashboards
Bonus lessons
Pulling data
Transforming data
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Course overview
Pulling data
Transforming data
Exporting data & dashboards
Bonus lessons
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Transforming data - bonus lesson

Removing duplicates

Using the Remove duplicates step, you can ensure your datasets are always free of duplicate values.  

How to use the step

  1. Drag a Remove duplicates step onto the canvas. 
  2. Specify which column(s) you want to check for duplicates within. 

Pro tip

  • In spreadsheets, to dedupe based on values in multiple columns, you might use a concatenate function to combine values from multiple columns. There’s no need to do this in Parabola — you can just select multiple columns, and Parabola will do the rest.

Visit our support docs to learn more about the step. 

Next lesson

Using the Remove Duplicate Rows Step in Parabola

The Remove Duplicate Rows step ensures that duplicate data is always handled properly, no matter how many duplicates exist in your dataset.

Different Ways to Handle Duplicates in Parabola

While this video focuses on removing duplicates, there are other ways to handle them in Parabola:
✅ Merge Duplicate Rows – Consolidate duplicates instead of removing them.
✅ Sum by Group / Count by Group – Aggregate values instead of deleting duplicates (e.g., sum all sales for a specific SKU).

Example 1: Removing Duplicates by SKU

  1. By default, Parabola removes duplicates based on the first column (e.g., "Product Title").
  2. Check Input 1 to view the original dataset.
  3. Select "SKU" as the column to deduplicate.
  4. Click Show Updated Results → The dataset is reduced from 38 rows to 37, removing one duplicate SKU.

Example 2: Deduplicating Based on Multiple Columns

In Excel, you might concatenate two columns before deduplicating. Parabola makes this process much simpler:

  1. Select both "SKU" and "Warehouse" as deduplication keys.
  2. Click Show Updated Results → The step now removes only rows where both SKU and Warehouse match.

This approach ensures that duplicate SKUs from different warehouses remain intact while cleaning up true duplicates.

Pro Tip: Choosing the Right Deduplication Strategy

  • If you want to remove duplicates, use Remove Duplicate Rows.
  • If you need to combine duplicate data (instead of deleting it), consider Merge Duplicate Rows.
  • If you want to sum or count duplicate entries, use Sum by Group or Count by Group.

Try It Yourself!

Test the Remove Duplicate Rows step in the building challenge below and let us know if you have any questions! 🚀