How to Leverage Metadata for Synthetic Data Generation

by Louie Flores on Mar 09, 2022

The market for Enterprise Metadata Management is forecast to reach $6.9 Billion by 2026 growing at a CAGR of 14% (Global Industry Analysts). The technology is used to centrally manage and deliver high quality data and trusted information for business analysis and decision-making.


Metadata provides a perfect data model for generating synthetic test data. That’s because metadata operates as a continuously updated template of the data structures and data relationships used by data sources across the enterprise. Now GenRocket allows software developers and test engineers to import JSON Schema files created by metadata management platforms like Abinitio and Alation to generate synthetic data based on those data definitions.

Synthetic Test Data Automation

Metadata can easily be exported from these metadata management platforms as JSON Schema files, and imported by GenRocket’s Synthetic Test Data Automation platform, and used to model test data projects that accurately reflect the data model of the source application or database.

It’s a streamlined and automated process that can be used and re-used for any number of Test Data Projects. And in each Test Data Project, Test Data Cases, the instruction sets used for real-time synthetic data generation can be designed to meet any number of test case requirements.

Read our latest blog article and learn how DevOps teams can greatly accelerate test cycle time and increase test coverage by leveraging metadata to generate comprehensive synthetic test datasets.