> ## Documentation Index
> Fetch the complete documentation index at: https://parabola.io/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# Transforming data
In this lesson, you'll learn the three broad categories of data transformations — calculations, business logic, and formatting — and see how to apply them in your flow.
***
With your shipments and delivery data combined, calculate expected delivery dates, flag late shipments, and filter down to only the shipments that missed their SLA by 2 or more days. Copy and paste this prompt into Parabola:
```text wrap theme={null}
First, calculate a new column called "Expected Delivery" by adding "SLA_Days" days to "Order_Date".
Then calculate a new column called "Days Late" as the number of days between "Expected Delivery" and "Delivery Date".
Next, add a "Delivery Status" column:
* If "Days Late" is greater than 0, set it to "Late"
* Otherwise set it to "On Time"
Finally, filter to only keep rows where "Delivery Status" is not blank.
```
The steps added to your canvas and their exact documentation may differ from what you see below — every AI response is unique. The important thing is that your resulting data set matches what you see here.
