Tanvi Mittal
Smart Test Data Engineering: AI, Privacy, and Automation for the Next Generation of Digital Systems
Abstract:
As enterprises accelerate digital transformation, the volume of operational data produced by modern systems especially in regulated sectors like banking has grown beyond human scale. Logs, telemetry, and user events contain the richest source of truth for testing, yet they also carry sensitive information that makes it difficult to use safely. Traditional test data practices cannot keep pace with this complexity, leading to blind spots in quality, security, and compliance.
This keynote explores a new paradigm: Smart Test Data Engineering, where AI, privacy engineering, and automation converge to convert raw system intelligence into actionable, safe, and high-quality test assets. The session will demonstrate how intelligent PII detection, differential privacy, automated journey reconstruction, and Gherkin-based scenario generation enable enterprises to build more resilient, scalable, and audit-ready digital systems. Real-world examples from secure environments will show how AI-driven pipelines can reconstruct customer journeys, identify high-risk flows, generate meaningful test cases, and enforce privacy without exposing sensitive data.
Attendees will gain a practical understanding of how next-generation intelligent systems can radically improve test coverage, reduce defects, and accelerate deliverywhile meeting modern expectations for data governance and regulatory compliance. Smart Test Data Engineering is not just an advancement in QA; it is an essential building block of future-ready, trustworthy enterprise computing.
Profile:
Tanvi Mittal is a Test Automation Specialist and AI-driven Quality Engineering leader with more than a decade of experience building intelligent, scalable, and privacy-aware testing solutions. She is the creator of LogMiner-QA, an innovative tool that transforms raw banking logs into safe, actionable test cases, and she holds a patent pending for its unique approach to PII detection, differential privacy, and automated journey-based test generation.
Tanvi’s expertise spans test automation strategy, AI-assisted quality engineering, data privacy in testing, and enterprise test transformation. She has been invited to speak at global conferences including WITCON, BrowserStack Meetups, Startup Cincy, Women in Tech events, and several AI and testing community sessions. Her articles on AI in QA, test data engineering, and women in tech leadership have been featured in Women in Tech, Medium, and other platforms.
Passionate about shaping the next era of intelligent QA, Tanvi mentors students and early-career professionals and actively advocates for smarter, safer, and more inclusive technology practices.