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Column-Level Lineage provides visibility into the upstream and downstream relationships of a column.

Common use-cases for column-level lineage are:

  1. Source Exploration: During development, column-level lineage helps you understand how a column is derived.
  2. Impact Analysis: When modifying the logic of a column, column-level lineage enables you to assess the potential impact across the entire DAG.
  3. Root Cause Analysis: Column-level lineage helps identify the possible source of errors by tracing data lineage at the column level.

Usage

  1. Select a node in the lineage DAG, then click the column you want to view.

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  2. The column-level lineage for the selected column will be displayed.

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  3. To exit column-level lineage view, click the close button in the upper-left corner.

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Transformation Types

The transformation type is also displayed for each column, which will help you understand how the column was generated or modified.

Type Description
Pass-through The column is directly selected from the upstream table.
Renamed The column is selected from the upstream table but with a different name.
Derived The column is created through transformations applied to upstream columns, such as calculations, conditions, functions, or aggregations.
Source The column is not derived from any upstream data. It may originate from a seed/source node, literal value or data generation function.
Unknown We have no information about the transformation type. This could be due to a parse error or other unknown reason.