If organizations are looking for fresh ideas for bringing synthetic test data into development, testing, and automation workflows without losing human understanding and control, this session offers a practical perspective.

Dag Nygaard and Erik Rogstad share how they approached test data generation in a large-scale microservice environment and how they made usable, consistent synthetic data available across the organization.

To make test data generation accessible to people with varying technical skills, they built a domain-specific language (DSL) for specifying test data. The DSL, coupled with organizational information models, allows developers, testers, and analysts to express intent in familiar terms at the level of abstraction they require.

Generators then transform these specifications into test data that populate test environments, integrate with automation frameworks, or create large, consistent datasets for performance and load testing.

This approach has been implemented at the Norwegian Tax Administration, where it has been adopted across all development teams. It provides a shared, centralized method for working with test data, eliminating the need for custom scripts and enabling teams to request the data they need when they need it.

The Norwegian Tax Administration has also released an open-source version as a foundation for automating test data generation.

Regardless of role, attendees will leave the session with practical insights and inspiration for implementing synthetic, on-demand test data solutions.