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Test Data Automation: Delivering Quality Data at Speed
Rigorous testing at the speed of today’s release cycles requires constant access to “good” data. That means data combinations with which to execute every positive and negative test scenario, available exactly when and where parallel test teams need it. The rich data must also be prepared at the speed with which parallelised automation burns through it and must be available on tap for each and every unique test case.

Rigorously testing at the speed of agile and DevOps therefore requires a new TDM paradigm, moving beyond just the logistics of “subset, mask, and clone” provisioning.

This interactive webinar will introduce a new paradigm in test data, one that is test-driven, self-service and automated. This new paradigm, “Test Data Automation” embeds a complete range of standardized TDM utilities within CI/CD pipelines and test automation frameworks, preparing complete test data “just in time” as tests are generated or executed. The automated “find and makes” provide the right data, for the right test, in the right environment, without any delays or gaps in the test data coverage.

Join Huw Price, a test data veteran with 35 years’ experience, to discover a practical strategy for moving towards “test data automation”. The live demo and discussion will show you how:
1. Test data holds the keys to make or break testing, touching upon agility, quality, and compliance;
2. Test data management has evolved from copying raw production data, to masking and subsetting, and now to "allocating" rich data combinations on the fly;
3. The rise of agile, automation, and GDPR present new test data challenges, that "logistical" approaches to TDM are often poorly equipped to tackle;
4. Today, on-the-fly data allocation can find, make and prepare data as tests are created and executed within CI/CD pipelines.

*By registering for this webinar, you agree to the privacy policy of Curiosity Software Ireland: https://curiositysoftware.ie/privacy-policy

May 12, 2020 02:00 PM in London

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