Foundational is a data management platform that provides automated, column-level data lineage across application code, data engineering pipelines, and BI visualizations, ensuring real-time visibility into the impact of code changes. It enables organizations to identify and prevent data issues before deployment, streamlining data contract enforcement and reducing the risk of pipeline failures.
Funding
$8M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
AVGVVVFounders
Product
Problem
Data teams face challenges in maintaining data quality and preventing pipeline failures due to code changes across complex application code, data engineering pipelines, and BI visualizations. Identifying the impact of code changes on downstream data assets is difficult, leading to potential data inconsistencies and errors. Enforcing data contracts across fragmented data stacks is also a manual and time-consuming process.
Solution
Foundational provides a data management platform that automates column-level data lineage across the entire data stack, offering real-time visibility into the impact of code changes. By integrating with Git repositories, Foundational enables data teams to identify and prevent data issues before deployment. The platform automates data contract enforcement, aligning data producers and consumers. Foundational analyzes source code, query logs, schemas, and metadata across every step in the data lifecycle to ensure comprehensive data quality.
Target Audience
Foundational is designed for data teams, data engineers, and data platform teams who need to ensure data quality, prevent pipeline failures, and enforce data contracts across complex data environments.
Features
- Automated, column-level data lineage across application code, data engineering pipelines, and BI visualizations
- Native Git integrations for seamless deployment across the entire organization
- Automated data contract enforcement to align data producers and consumers
- Analysis of source code, query logs, schemas, and metadata across the data lifecycle
- Real-time visibility into the impact of code changes on downstream data assets
- Automated setup with zero code or configuration changes needed