Influence Of Artificial Intelligence & Machine Learning In Test Data Management
summary
Claim: AI/ML cuts the half of testing effort spent on sourcing and cleaning data by automating discovery, masking and generation. Demonstrations use open source TD spora to train on ~11 production rows and then generate hundreds of synthetic rows that preserve attribute ratios, and an agent platform (Elita/Alita) to inject that CSV into generated test cases and runnable Python automation, producing a simple pass/fail report. Expect model training time, configurable epochs, and human review for PI/edge-case accuracy.
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chapters (9)
- 0:00AI and ML in TDM
- 3:38Legacy data masking
- 6:52Synthetic data benefits
- 8:58AI replication from production
- 10:32Demo: TDSPora synthetic data
- 24:05AI agents for test cases
- 31:33Automating scripts with AI data
- 37:38AI in TDM future
- 42:03Q&A
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