Along with the 4 Dollar, 3 Penny principle, the below given tenets should also be implemented for a good TDM strategy:
Secure at source
Data copied from production should be masked before landing in non-prod environments. On the fly masking should be adopted complying with regulatory and local laws. There are multiple TDM tools that adopt this process.
DevOps, Agile adaptability
Test data creation and provision should support DevOps and Agile methodologies leveraging test-driven data creation frameworks. This requires faster turnaround of data refresh, masking and creating ad hoc data requests to support ongoing testing activities.
Data request should be catered to all stakeholders as on-demand service delivery. The stakeholders can be developers, users, testers, data base administrators, data SME. This self service should help to reduce the turnaround time for refreshing the entire data/selected data set, provision only masked data, do periodic refreshes to golden copy, archive and backup the data. All these services should be provided as a service and catalogue based delivery model.
Synthetic data adoption
Programs should adopt ways and means to create dynamic data or synthetic data to cover out layered scenarios or negative scenarios that cannot be tested using existing production data. These synthetic data can be created using licensed tool/open source tools/simple scripts using .Net/Java platform.
Support to all testing phases
Test data should cater to all types of testing including functional, regression, automation, performance and user acceptance testing. Framework should support the development team to populate required data to unit test environments as well.
The future of test data management
Test data is traditionally dependent on production data with exceptions to use sensitized data in test environment. With improvements in technology, we see many open source companies and third party tool vendors adopting synthetic data, as it is more convenient and useful to create data for Agile/DevOps programs. Service virtualization supports creation of test stubs and complements TDM tools. Dependency on production data should be reduced as it involves huge turnaround time including masking sensitive data. The overall focus should be on leveraging the power of synthetic data generation, supplemented with service virtualization methodologies. We can still leverage production data to replicate any critical scenarios that need to be recreated in lower environments.