Overcoming Challenges Data Quality With AI

Описание: In this video, we discuss the common challenges faced in ATL testing, from low QA-to-developer ratios to the complexities of handling diverse and massive data sets. Learn how AI and ML are stepping in to automate repetitive tasks and enhance coverage, making data validation more efficient and error-free.

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Handling diverse data sources like CSV files, RSS feeds, APIs, and various databases can be complex and time-consuming. With AI/ML, we can automate these tedious tasks, increasing test coverage and reducing errors.
You'll learn:
✅ Common challenges in ATL testing, including low QA-to-developer ratios and tight deadlines
✅ How diverse data formats complicate data validation
✅ How AI and ML can automate tasks, improving efficiency and coverage

If you're a QA engineer or developer, this video will show you how leveraging AI/ML in ATL testing can help streamline your process and reduce manual errors.

#ATLTesting #DataValidation #TestAutomation #AIinTesting #MachineLearning


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