{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/27639b429faa46eaa9ce0c40138d37d7\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/27639b429faa46eaa9ce0c40138d37d7-aee9c23c08f61992.gif","duration":231.797,"title":"Skipper Pipeline Lineage, Column Impact Analysis","description":"This Loom demonstrates Skipper’s new end to end lineage feature with column level impact analysis across pipelines. It builds a lineage graph from source data in S3 JSON files through raw data lakes, dbt aggregations, and into silver and gold dashboards. The example traces the bike ID field as it propagates through missing value and data quality indicators and how it becomes distinct count metrics in gold data. The discussion emphasizes that Skipper metadata supports schema discovery and backward compatibility, helping you understand downstream effects before changing upstream fields."}