Loading content
Strategy and practice for provisioning, maintaining and governing datasets for testing, including generation, masking, subsetting and versioning.
Test Data Management is the discipline of designing, provisioning and maintaining datasets used for software testing. It covers synthetic data generation, masking, subsetting, versioning and provisioning for environments to ensure repeatable, privacy-compliant tests. TDM balances realism, cost and compliance across development, CI and production-like testing pipelines.
Time from request to availability of test data in the target environment.
Share of test runs executed with realistic or sufficiently simulated data.
Number of incidents where test data violated privacy requirements.
Production subsets are masked and versioned to meet regulatory requirements while enabling integration tests.
Large synthetic product catalogs are generated to validate search and filter functionality under realistic loads.
Patient data is pseudonymized and provided in a controlled way to run tests without exposing personal information.
Inventory: data sources, classification and sensitivity
Define policy: masking, subsetting, versioning
Select tooling, implement automation and integrate into CI