What is the difference between table-level and column-level data lineage?

Table-level lineage shows that Table B was derived from Table A. Column-level lineage shows that specific_column in Table B was computed from column_x in Table A through transformation Y — enabling precise impact analysis (what breaks if column_x changes?) and compliance reporting (where does this PII field flow?).

How does OpenLineage standardize data lineage collection across tools?

OpenLineage is a CNCF-hosted open standard that defines a common specification for lineage events emitted by data pipelines. Integrations exist for Apache Airflow, Apache Spark, dbt, Great Expectations, and Flink. Platforms like Marquez, Atlan, DataHub, and Microsoft Purview consume OpenLineage events, enabling portable lineage across the entire data stack.

How do enterprises use data lineage for regulatory compliance?

GDPR Article 30 requires records of processing activities including data flows. BCBS 239 mandates data lineage for risk data reporting in banks. Data lineage platforms enable compliance teams to trace the flow of personal data from collection to deletion, identify all systems storing regulated data, and demonstrate data processing impact to auditors.

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Best Solutions for Data Lineage Platform

Expert analysis of the best data lineage platforms for tracking data flow and impact analysis, comparing Atlan, Marquez, DataHub, Collibra, and cloud-native lineage solutions.

Frequently Asked Questions

Atlan provides automated lineage across dbt, Fivetran, Snowflake, and BI tools with a visual graph interface. DataHub (open-source, LinkedIn) offers production-grade lineage with REST API. Marquez implements OpenLineage standard natively, enabling vendor-neutral lineage collection from Spark, Airflow, dbt, and other frameworks.

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