Database Subsetting | Enterprise Test Data

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Reduce the size of non-production data sets while retaining data variations and relationships needed for rigorous testing. Test Data Automation extracts referentially-intact, coverage-complete subsets on demand, shortening testing cycles, minimising storage costs, and finding bugs at less cost to fix.

Watch the two-minute overview of Data Subsetting from Test Data Automation, to see how:
1. Test Data Automation provides granular methods for reducing the size of data sets, while retaining the relationships and variations needed for testing and development.
2. The concise subsetting avoids runaway non-production storage costs, crawling iteratively across data to collect just enough interrelated data to create referentially intact data sets.
3. Three types of subsets reduce the size of data without reducing variety, collecting data to fulfil individual scenarios, to fulfil specified criteria, or to shrink data while retaining its variations.
4. A self-service portal avoids data provisioning bottlenecks, enabling testers, developers and automation frameworks to self-provision the subsets they need in parallel and on demand.
5. Integrating subsetting with database virtualisation provides data sets at a fraction of the cost of making physical copies, creating virtual copies in seconds for parallel teams and technologies.
6. Testing with concise subsets reduces run times and produces less-cumbersome run results to analyse, further shortening release cycles and optimising the use of non-production resources.
7. Testing and developing with the smallest possible data set can support legislative compliance requirements around data minimisation, reducing the risk of devastating fines.