Foundational is a data lineage platform that analyzes source code to map how data flows across modern data stacks. It provides column level and end to end data lineage with impact analysis across transformations, warehouses, analytics, and production AI systems so teams understand changes before they ship.
Data lineage spans the entire data stack, from source systems to analytics and AI.
Data lineage describes how data moves, transforms, and is consumed across systems. Modern data lineage shows where data originates, how it changes through transformations, and which downstream tables, dashboards, and AI models depend on it. Data lineage platforms use this information to help teams understand dependencies, assess impact, and operate data systems with confidence.
Traditional data lineage solutions rely on partial, out-of-date data such as query logs, and are therefore inaccurate and limited to SQL only. Foundational goes directly to source code and understands every part of the stack, from upstream applications to downstream dashboards
Automate lineage across warehouses, Airflow jobs, Spark and others
Track dependencies to upstream applications in any framework
Lineage is always updated to the latest commit
Developers typically do not understand data dependencies outside of their local project. With Foundational, data lineage makes upstream and downstream dependencies visible across every tool and data product. This allows developers to understand downstream impact before changes reach production, eliminating unknowns when making updates that affect downstream consumers.
Foundational integrates directly with version control to surface data lineage in pull requests
Every pull request impacting data gets validated
Data producers and consumers can easily validate new code changes
Foundational supports the full set of data lineage types required to operate modern data and AI platforms with confidence.
Column level data lineage: Track how individual fields are created, transformed, and propagated across tables, models, and downstream assets.
End to end data lineage: Map data flows from source systems through transformations to analytics, dashboards, and consumption layers.
Code based data lineage: Generate lineage directly from SQL, dbt, and transformation logic rather than inferring relationships from metadata or logs.
Change impact lineage: Understand the downstream impact of code changes and pull requests before deployment using lineage driven impact analysis.
Analytics and AI lineage: Connect data sources and transformations to reports, metrics, and AI model inputs to ensure trusted and governed consumption.
Understanding what data lineage is and why it matters is only the first step. The effectiveness of a data lineage platform depends on how lineage is generated, maintained, and applied in real workflows.
Foundational implements data lineage by analyzing source code across the modern data stack to produce accurate, continuously updated lineage that reflects how data actually moves and transforms. This approach enables teams to move beyond static diagrams and use lineage operationally for impact analysis, incident prevention, and governance.
You’ll be up and running in under an hour: Schedule a quick call, connect us to your code, and get unmatched insights, immediately.
Find and prevent data issues, cost deficiencies, and privacy risks. Foundational can be deployed in less than an hour.
