
The unique regulatory landscape of healthcare requires that every automated decision in a data pipeline be accompanied by interpretability and clear feature attribution. For decades, data engineering followed a predictable pattern of extracting, transforming, and loading data into static warehouses for basic reporting. However, as the volume and complexity of clinical and administrative data explode, these traditional methods are no










