Datafold provides a unified platform for proactive data quality management through automated CI testing, machine learning-powered monitoring, and cross-database data reconciliation. The solution enables data teams to prevent quality issues and accelerate data migrations, resulting in significant time savings and improved accuracy across workflows.
Funding
$22.2M 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.
ACEVVVFounders
Product
Problem
Data teams face challenges in maintaining data quality across complex workflows, leading to errors, delays, and inaccuracies. Traditional methods often fail to detect data regressions and anomalies before they impact production systems. Migrating data between databases is time-consuming and prone to errors, requiring extensive manual validation.
Solution
Datafold offers a unified platform for proactive data quality management, leveraging automated CI/CD testing, machine learning-powered data monitoring, and cross-database data reconciliation. The platform enables data teams to prevent data quality incidents, accelerate data migrations, and improve overall data accuracy. By integrating with existing data stacks, Datafold provides end-to-end data observability, allowing users to identify and resolve issues before they impact downstream processes. The solution supports various deployment options, including multi-tenant, dedicated cloud, and on-premise, ensuring flexibility and security.
Target Audience
Datafold is designed for data engineers, data architects, data analysts, and data scientists who need to ensure data quality across their workflows and accelerate data migration projects.
Features
- Automated CI/CD testing to prevent data quality regressions during code deployments
- ML-powered data monitoring to detect anomalies and data quality incidents in real-time
- Cross-database data reconciliation to ensure data consistency during migrations
- AI-powered SQL conversion to accelerate data migration projects
- Column-level lineage to track data dependencies and identify potential impact areas
- Data diffing capabilities to understand how data changes with code updates
- Role-based access control (RBAC), single sign-on (SSO), and SAML integration for secure access
- Flexible deployment options: multi-tenant, dedicated cloud, and on-premise
- Integrations with 50+ popular data tools