Explore the Lineage View

Explore lineage diagrams interactively to understand how data flows between sources, transformations, and dashboards.

Explore the Lineage View

Collate displays end-to-end lineage for the table and column levels, for Database, Dashboard, and Pipeline assets. Search for a data asset and expand the graph to see its lineage:

• Each node expands to show its upstream and downstream edges.
• Each edge carries details such as the SQL query, pipeline information, and column-level lineage.

Source, Target, and Edges

In the example below:

• The table on the left is the parent, or Source node.
• The table on the right is the Target node, identifiable by the arrow pointing into it.
• The arrow connecting them is the Edge.

Click an edge to see its details: the Source, Target, Description, and SQL Query. For a view, the SQL query shows how the target was generated from the source.

Metadata ingestion also brings in view lineage, if the database has views (data assets of the type View).

Lineage Config

Control how many upstream and downstream nodes appear in the graph. This only affects your current view: it resets to the platform default the next time you open a lineage graph.

To configure the lineage nodes, follow the steps below:

1. Click the Setting icon.

   

2. Set the following fields:

   • Upstream Depth: Number of upstream hops shown by default when opening a lineage graph, to identify parent-level sources.
   • Downstream Depth: Number of downstream hops shown by default when opening a lineage graph, to identify child-level targets.
   • Nodes Per Layer: Maximum number of nodes shown per layer. There’s no fixed maximum here. If a layer has more nodes than this, the rest are paginated instead of all being rendered at once.
   

To change the default that applies for every session, see Lineage.

Impact Analysis View

The Lineage page has two tabs at the top: Lineage (the graph you’ve seen so far) and Impact Analysis, a table that lists the same upstream and downstream assets as rows instead of nodes on a graph. This is easier to scan, search, and sort when an asset has a large number of dependencies.

• Upstream / Downstream: Switch direction. Each option shows a count of how many assets lie in that direction.
• Impact On: Choose whether the table lists Asset Level impact (one row per table, pipeline, dashboard, and so on) or Column Level impact (one row per source-to-target column mapping).
• Customize: Choose which columns to show. Name (or Source/Impacted Column, in Column Level mode) always stays visible. Every other column can be toggled off.

Search narrows the rows by asset name (Asset Level) or column name (Column Level).

Asset Level columns: Name, Node Depth (number of hops from the asset you’re viewing), Description, Domains, Owners, Tier, Tags, and Glossary Terms.

Column Level columns: Source, Source Column, Impacted (the downstream or upstream asset), Impacted Column, plus the same Node Depth, Description, Domains, Owners, Tier, Tags, and Glossary Terms columns.

Data Asset Details

Click a data asset to view its details:

• Source, Name, Description, Owner (team/user), Tier, and Usage information.
• Additional details based on the type of data asset (Table, Topic, Dashboard, Pipeline, ML Model, Container). For example, a table’s type, number of queries, and columns.
• Data quality and profiler metrics, including tests passed, aborted, and failed.
• Tags associated with the data asset.
• Schema details: column names, column types, and column descriptions.

Column-Level Lineage

Click a table to expand its list of columns and see column-level lineage.

Pipeline and Dashboard Lineage

For Pipelines:

• Lineage first comes from the metadata ingested from the databases.
• Setting up pipeline ingestion with a database service name links the pipeline to the database tables it reads from and writes to.
• If a pipeline creates the lineage, that shows up in the edge information too.

Dashboards work the same way:

• Lineage first comes from the metadata ingested from the databases.
• Dashboard ingestion then adds the data models and charts, linking them back to the database tables they’re built on.

Lineage Layers

Switch between layers to explore different dimensions of your data’s lineage.

Column Layer

Trace individual fields — like customer_id or first_name — as they move across tables and pipelines. The column layer shows exactly how each attribute transforms along the way.

Observability Layer

See data quality results directly in the lineage graph — test passes, failures, and pending checks appear on each node. This helps you quickly spot which assets in the pipeline have quality issues.

Service Layer

See how data moves across services — from Hive to Redshift to Power BI to Tableau. The service layer gives you a system-level view of the full data journey, from ingestion through transformation to consumption.

Domain Layer

Group assets by business domain — like “Ecommerce” or “Customer Data” — to understand lineage in business terms. This view connects your technical assets to the business functions they support.

Data Product Layer

See the lineage of your curated, consumption-ready data products — like Customer Registry or Superstore. The data product layer shows which trusted outputs belong to which domain and where they come from.

How Column-Level Lineage Works

Explore and edit the rich column-level lineage.