DataHub provides a modern data catalog and metadata platform that transforms enterprise data into trusted context for both users and AI agents. It offers unified capabilities across data discovery, observability, and governance to improve data reliability and efficiency. The platform helps organizations quickly find data, resolve quality issues using lineage, and reduce infrastructure waste by identifying unused assets.
Funding
$35M 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.
5OFounders
Product
Problem
Enterprises struggle to locate, understand, and trust the vast amounts of data spread across multiple systems, leading to slow decision-making, data quality incidents, and wasted infrastructure resources.
Solution
DataHub provides a modern data catalog and metadata platform that creates a unified context layer for both human users and AI agents. By aggregating metadata, lineage, and quality metrics, it enables rapid data discovery and confidence in data usage. An integrated AI chat assistant leverages this context to help users troubleshoot data quality issues and resolve metric discrepancies more efficiently. The platform also offers proactive monitoring and impact analysis to identify unused pipelines and redundant assets, helping organizations reduce data infrastructure costs and prevent costly errors.
Target Audience
Primary customers are data engineering, analytics, and data science teams within large enterprises that need reliable data discovery, governance, and cost optimization.
Features
- Centralized metadata repository with automated ingestion from diverse data sources
- Full data lineage visualization that maps dependencies across pipelines and datasets
- AI-powered chat interface for natural-language queries, debugging, and quality issue resolution
- Proactive data quality monitoring with alerts for anomalies and policy violations
- Impact analysis tools to detect unused pipelines, redundant data, and change consequences
- Role-based access controls and integration hooks for existing data governance workflows