Gable provides a data change management platform that registers data assets and automatically generates data contracts to enhance collaboration between development and data teams. By notifying data teams of changes that impact downstream users, Gable prevents data quality issues and operational outages across various data sources.
Funding
$24.8M 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.
Founders
Product
Problem
Data quality issues and operational outages often stem from a lack of visibility into data changes at the application level, leading to disruptions for downstream users and inefficiencies in data management. Traditional methods lack automated mechanisms to detect and manage these changes proactively.
Solution
Gable offers a data change management platform that addresses these challenges by registering data assets directly from application code and data sources. The platform automatically generates data contracts, fostering collaboration between development and data teams. By providing notifications of changes that impact downstream users, Gable enables proactive prevention of data quality issues and operational outages across various data sources. Gable integrates directly into existing build and deployment systems, providing pre-deployment issue detection and real-time compliance monitoring.
Target Audience
Gable's primary customers are data engineers, data platform teams, and software engineers who need to ensure data quality and prevent outages by managing data changes at the application level.
Features
- Static code analysis to detect data-producing code in languages like TypeScript, Python, Java, and Swift.
- Automated data contract generation based on scanned repositories.
- Real-time notifications to developers regarding changes that violate data contracts or affect downstream dependencies.
- Source repository and CI/CD integration for seamless integration into existing workflows.
- Data dependency mapping to understand the downstream impact of changes and accelerate root cause analysis.
- Governance and policy as code to ensure consistent data governance across teams.
- Automatic real-time compliance monitoring to detect issues early and avoid potential regulatory violations.