Data lineage isn’t new, but automation has finally made it accessible and scalable—to a certain extent.
In the old days (way back in the mid-2010s), lineage happened through a lot of manual work. This involved identifying data assets, tracking them to their ingestion sources, documenting those sources, mapping the path of data as it moved through various pipelines and stages of transformation, and pinpointing where the data was served up in dashboards and reports.
