In many analytics platforms, there are performance issues that do not always come from complex transformations. Sometimes the bottleneck is much simpler: the same large datasets are being read repeatedly from remote storage.This pattern is common in shared analytics environments. A data engineering job reads a curated dataset to build aggregates. A BI refresh reads the same table again. A data science notebook filters the same records during exploration. Another scheduled workflow joins against the same reference data several times during the day.