A tour of test data generation using Test Data Automation: On demand data journeys for complex systems

Overcome system complexity and de-risk rapid system change, auto-generating consistent data journeys for end-to-end testing. Test Data Automation publishes rich data consistently across databases, files and messages, triggered during manual and automated processes for rigorous testing in-sprint.

Traditional Test Data Management is no match for system complexity

Faced with unprecedented system complexity and more requests than ever, traditional test data management can’t keep up. Testing requires data that links across numerous components, APIs and back-end systems. This complex data must be consistent as otherwise tests fail and must also be varied enough to test a wide range of data journeys.  Yet, it must also be available to multiple teams and frameworks in parallel, all within the confines of ever-shorter iterations. Testers today can no longer rely on a siloed team to fulfil data requests, and nor can that team create data quickly for every dependency. An automated approach is instead needed to allocate complex data in time for in-sprint testing.

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Test Data Automation: Complex data at the speed of test automation and CI/CD

Watch this demo for a tour of the test data generation techniques used by Test Data Automation to create on-the-fly data during test execution and CI/CD processes. The flexible data generation creates data simultaneously in databases, messages, systems and files, providing consistent data journeys for complex system testing. The data can further be masked for compliance as it moves, while applying subsetting and data cloning to provide the right volume and variety of data needed for complete testing. Meanwhile, visual data flows apply sophisticated coverage algorithms to generate a comprehensive sets of data journeys, pushed automatically to test management and automation tools for in-sprint testing.

Synthetic Test Data Generation using Test Data Automation

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Together, these flexible and fully integrated technologies generate all the linked-up data needed to test complex systems in-sprint, triggered automatically as part of CI/CD pipelines and test execution. Each process is easy to set-up and combine, selecting from parameters in simple configuration spreadsheets. Every test data publish can furthermore be re-used from an online test data catalogue, selecting from intuitive parameters in online forms. Instead of relying on an overworked provisioning team, developers, testers and automation engineers can generate the data they need, on demand or as part of test execution.

Accelerators and connectors for generating accurate data as tests run

Watch this demo to see how Test Data Automation integrates seamlessly with a range of CI/CD and test automation technologies, generating data across databases, files, messages and systems. This example of data generation for SQLServer, Maria DB, CSV and JSON will show you how:

  1. Test Data Automation publishes interrelated data to different databases, files and message types, creating consistent data for testing complex systems.
  2. An online test data catalogue makes it easy for testers and developers to generate the data they need on demand, allowing parallel teams to test in-sprint.
  3. Test Data Automation jobs can be triggered on demand or can be embedded within existing automation to eliminate data provisioning bottlenecks.
  4. The high-speed test data generation seamlessly combine test data technologies, including generation, masking, subsetting and cloning.
  5. Combining generation with masking mitigates against the risk of costly non-compliance, while subsetting reduces test run time and test result analysis.
  6. Automated data cloning bulks data as it’s published, producing the combinations needed for teams and tests to work in parallel.
  7. Configuring the publishes for each data target is quick and simple, automatically generating a simple-to-use configuration spreadsheet and filling in parameters.
  8. A range of intuitive functions retain relationships within and across databases, passing values from one publish to the next to create consistent data journeys.
  9. Generating matching message data is as easy as attaching a template file to the configuration spreadsheet, mirroring values generated into databases and files.
  10. Test Modeller automatically converts the configuration file into a visual data flow, building equivalence classes to generate a rich spread of values.
  11. Automated coverage algorithms generate a complete spread of values from the flows, producing the data needed to rigorously test complex systems in-sprint.
  12. Generating data automatically links it to test cases in tools like Jira, ALM/Octane, Zephyr and Azure DevOps, as well as to Gherkin feature files.
  13. Test Modeller automatically commits data publishes to Git repositories, easily restoring previous versions to generate the right data on demand.
  14. Triggering test data generation from CI/CD tools like Jenkins is as easy as downloading the DevOps connector from Test Modeller, allocating rich test data on-the-fly.

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