Lineage is the foundation of the Context Engine — it’s how Elementary maps your entire data stack, from ingestion sources through transformations to BI and downstream consumers. Every asset, test result, and health signal is connected through this graph, which is what allows the AI Agent and MCP to reason across your stack. Elementary builds column-level lineage automatically from your data warehouse metadata and integrations with dbt, BI tools, Python pipelines, and other sources. The graph is updated frequently so it reflects your current state.Documentation Index
Fetch the complete documentation index at: https://docs.elementary-data.com/llms.txt
Use this file to discover all available pages before exploring further.
What’s included in the lineage graph
Elementary connects assets across your full stack:- Ingestion sources — tables from your data warehouse, including those loaded by tools like Fivetran, and non-dbt assets synced directly from your warehouse
- dbt models and sources — resolved from your dbt project metadata
- Python SDK assets — tables and datasets produced by Python pipelines instrumented with the Elementary Python SDK
- BI and downstream tools — dashboards and exposures from Looker, Tableau, and other connected BI tools
- Semantic views — Snowflake Semantic Views connected to their underlying physical tables
What you can do with it
- Trace root causes — follow failures upstream to find where an issue originated
- Assess impact — see which downstream assets and dashboards are affected by a failure or change
- Prioritize triage — surface issues affecting critical or high-traffic assets first
- Detect unused datasets — identify assets with no downstream consumers to reduce cost
- Plan changes safely — understand what breaks before you make a change
Node info and test results
Select any node in the graph to see:- Test results — latest test results for that asset
- Node info — description, owner, tags, and job info if collected