Data processing across systems relies on data lineage, a crucial aspect that tracks the movement and transformation of data records. Data lineage is necessary for Data Operations and Governance that support incident response, legal investigations, and privacy and compliance standards. However, things can go wrong due to the proprietary hand-coded business logic that alters the data. When that happens, the current data lineage systems that operate at the dataset/table level are not very helpful. They require additional analysis effort that can be expensive and time-consuming. In today's data landscape, we need a record-level lineage that can pinpoint the exact source and cause of data issues with minimal manual intervention. This problem has long been neglected due to its complexity, but we have a solution to propose. In this presentation, we will introduce a novel concept and its reference implementation using Starburst Enterprise Platform.