Test Data is make or break for parallel testing and development
Today, there is a greater-than-ever need for parallelisation in testing and development. “Agile” and iterative delivery practices hinge on teams...
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For many organisations, test data “best practices” start and end with compliance. This reflects a tendency to focus on the problem immediately in front of us. “The business” or legislation have called for the removal of sensitive data from non-production environments; so, that’s the fire that organisations strive to put out first.
Though typically necessary, removing sensitive data from non-production environments overlooks two of the biggest challenges associated with test data today. First, it does not help with the immense time that testers and developers spend waiting for, finding, and making test data. Second, it overlooks the impact low-variety production data has on overall test coverage. To solve all three test data challenges – speed, quality, and compliance – a new strategy is needed.
I’ll be joining Paul Hammersley of EPI-USE Labs to discuss how organisations can target all three of these test data challenges. You can sign up to watch on demand. This blog will highlight some of the test data pressures that we will help resolve on the live webinar, while indicating the solution that we will discuss then.
Many organisations today must re-think their strategy for test data “management”. Relying on a central team to anonymise and copy large production data sets will always be a game of catch-up. Meanwhile, it does nothing to improve the quality of the data for testing, and nor does it reduce the time teams spend wading through large data sets or making missing combinations by hand.
Some of the challenges associated with a typical test data strategy today.
A range of factors have increased the demand for test data, adding to the urgency of a strategy re-think. These related trends have made it harder than ever for manual data provisioning to provide data of sufficient variety, at the speed demanded by parallel teams and frameworks. They include:
These related trends mean that today data of a greater variety is needed faster than ever before. They call for a modernisation of test data “best practices”, avoiding the significant bottlenecks that can raise in a world of rapid development, automated testing, and CI/CD.
Test data practices today need to be brought into line with the “best practices” found across DevOps and CI/CD pipelines. “Provisioning” data must be automated and parallelised, as well as capable of responding to changing requests on-the-fly. Both automated and manual data requesters must further be capable of triggering the reusable processes on demand, easing the pressure on an overworked data provisioning team.
Fortunately, there are today many effective tools and techniques that address different problems associated with test data. They include data masking to support compliance, generation to boost data variety, and data cloning to make data available to parallel tests, testers, and environments. Database virtualisation has further minimised the time and costs associated with copying data, while data comparisons and analysis engines help testers and developers understand data.
You likely already have some of these solutions at your organisation, either built in-house or using commercial tools. The missing piece in many test data strategies is the process by which the different tools can be combined, reused, and made available on demand to manual and automated data requesters. Too often, responsibility is instead pushed back onto an over-worked provisioning team, who adjust and slowly run a set of linear processes for each data request.
A two-stage modernisation strategy for test data accordingly looks as follows:
A two-stage modernisation strategy for test data
In other words, a complete test data strategy must comprise all the technologies needed to create complete and compliant data in parallel and on demand. These techniques must furthermore be standardised and automated, while also being exposed to parallel teams, automation frameworks and CI/CD pipelines. Manual and automated data requesters must be capable of parameterising and triggering reusable test data processes on demand, receiving the data they need on-the-fly.
I’ll be joining Paul Hammersley of EPI-USE Labs to explore how organisations can move from supporting test data compliance to implementing a modern test data strategy. To see how complete and compliant data can be made available on-the-fly, Testing across SAP and non-SAP systems: From test data compliance to continuous innovation.
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