Update website/docs/sql-reference/joins/sql-left-join.md

website/docs/sql-reference/joins/sql-left-join.md

@@ -73,4 +73,4 @@ Left joins are a fundamental in data modeling and analytics engineering work—t
 Something to note if you use left joins: if there are multiple records for an individual key in the left join database object, be aware that duplicates can potentially be introduced in the final query result. This is where dbt tests, such as testing for <Term id="primary-key" /> uniqueness and [equal row count](https://github.com/dbt-labs/dbt-utils#equal_rowcount-source) across upstream source tables and downstream child models, can help you identify faulty data modeling logic and improve data quality.
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-Where you will not (and should not) see left joins is in [staging models](https://docs.getdbt.com/best-practices/how-we-structure/2-staging) that are used to clean and prep raw source data for analytics uses. Any joins in your dbt projects should happen further downstream in [intermediate](https://docs.getdbt.com/best-practices/how-we-structure/3-intermediate) and [mart models](https://docs.getdbt.com/best-practices/how-we-structure/4-marts) to improve modularity and <Term id="dag" /> cleanliness.
+Where you will not (and should not) see left joins is in [staging models](/best-practices/how-we-structure/2-staging) that are used to clean and prep raw source data for analytics uses. Any joins in your dbt projects should happen further downstream in [intermediate](/best-practices/how-we-structure/3-intermediate) and [mart models](/best-practices/how-we-structure/4-marts) to improve modularity and <Term id="dag" /> cleanliness.