Achieve High Quality by Removing Misaligned Data with Data Cleansing

Transformations:
fill, delete, select

Do you ever have misaligned columns of data? This is a common data cleansing and quality scenario where columns of data are either shifted to the left or right from their intended position from the header or leading rows. This happens sometimes due to having ingested a printed or report view of the data.

This example template shows how you can fix such scenarios by using the fill transformation to fill up and down the rows and then filtering out any rows that have null values in those misaligned columns. You can leverage this technique to cleanse any shifted columns of data in your use case.

For more information, please see transformation function documentation for fill.