diff --git a/_docs/_user_guide/data_and_analytics/cloud_ingestion/sync_catalogs_data.md b/_docs/_user_guide/data_and_analytics/cloud_ingestion/sync_catalogs_data.md
index 71db272ed3c..1af6c2030da 100644
--- a/_docs/_user_guide/data_and_analytics/cloud_ingestion/sync_catalogs_data.md
+++ b/_docs/_user_guide/data_and_analytics/cloud_ingestion/sync_catalogs_data.md
@@ -173,7 +173,9 @@ CREATE TABLE `BRAZE-CLOUD-PRODUCTION.INGESTION.CATALOGS_SYNC`
 
 ## How the integration works
 
-Each time the sync runs, Braze will pull in all rows where `UPDATED_AT` is after the last timestamp synced. We recommend creating a view from your catalog data to set up a source table that will fully refresh each time a sync runs. For example, if you have a table of product data (`product_catalog_1`) with `product_id` and three additional attributes, you could sync the below view:
+Each time the sync runs, Braze will pull in all rows where `UPDATED_AT` is after the last timestamp synced. We recommend creating a view in your data warehouse from your catalog data to set up a source table that will fully refresh each time a sync runs. With views, you won't need to rewrite the query each time.
+
+For example, if you have a table of product data (`product_catalog_1`) with `product_id` and three additional attributes, you could sync the below view:
 
 {% tabs %}
 {% tab Snowflake %}