diff --git a/website/docs/terms/data-wrangling.md b/website/docs/terms/data-wrangling.md
index 4a26507adfd..58034fe8e91 100644
--- a/website/docs/terms/data-wrangling.md
+++ b/website/docs/terms/data-wrangling.md
@@ -37,7 +37,6 @@ Structuring your data is a type of transformation that involves reformatting and
 
 - Is your data in the format you need to perform analysis on it? Does your data need to be potentially unnested? *Should you nest or objectize columns together?*
 - Do the column names and values look correct for your use case?
-Do the column names and values look correct for your use case?
 
 If your data is not in a format that is usable, you can look into different solutions such as pivoting or using different functions to unpack lists and JSON files so that they are in a tabular format. Pivoting is helpful because it allows you to change the way your dataset is structured by rearranging the way columns, rows, and their values are displayed. dbt has a [pre-built macro](https://github.com/dbt-labs/dbt-utils/blob/main/macros/sql/pivot.sql) that makes pivoting less of a headache and more of a breeze.