The ultimate guide to data lineage in dbt

Data lineage is the process of tracking data from its origin to its destination, including all transformations and movements in between. It provides a detailed map of how data flows through an organization’s pipelines and how it impacts downstream systems. Techniques for capturing data lineage include metadata management, data profiling, and data mapping. dbt automates data lineage by using its dependency graph, which maps the relationships between different nodes, such as sources, models, snapshots, and metrics. Data lineage in dbt provides visibility into how data flows, transforms, and is used across your analytics pipeline. It enables clear visualization of dependencies, easier debugging and maintenance, and simplified collaboration among teams.

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