video1.0<iframe src="https://www.loom.com/embed/cf82e6a7ab824d8dbd572d9371ccf6dc" frameborder="0" width="1280" height="960" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>9601280Loomhttps://www.loom.com9601280https://cdn.loom.com/sessions/thumbnails/cf82e6a7ab824d8dbd572d9371ccf6dc-1692117390401.gif300.16666666666686In this video, I analyze the issue of duplicate data in Air Table records. By examining the source record ID and URL, I confirm that the duplicates are caused by individual feeds pointing to multiple records. I also discover variations in the source record ID, some being null and others having different values. To understand the scale of the issue, I observe that most of the duplicates are from 2022, indicating that it is historical data. This suggests that it is not a recurring bug but rather a data handling challenge. I also explore the prevalence of the issue by checking the number of implicated feeds. Overall, this investigation helps us understand the nature and scope of the duplicate data problem.