video1.0<iframe src="https://www.loom.com/embed/e57a163ecd8c4b15af0959fb0b4ab3eb" frameborder="0" width="1280" height="960" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>9601280Loomhttps://www.loom.com9601280https://cdn.loom.com/sessions/thumbnails/e57a163ecd8c4b15af0959fb0b4ab3eb-00001.gif241.49999999999994In this video, I continue from the previous one where we found the SQL and Jupyter. Now, we will run that SQL in BigQuery to understand the issue with the failing rows. I copy-paste the SQL into the BigQuery console and run it. The results show that there are 38 keys with duplicate values, but this is not enough to investigate meaningfully. I explain that dbt tests are generic and may require writing our own SQL. I demonstrate how to identify and left join the duplicates back onto the table to get more context. Join me as we investigate the failing rows in BigQuery.