I'm struggling to integrate ETL pipelines across multiple databases, APIs, and third-party tools. What's been the biggest integration challenge you've faced, and how did you overcome it?
As a tester, how do you ensure data quality in AI applications when traditional ETL validations, such as row counts, don't guarantee data accuracy or relevance?
Are there any trending and effective tools that are beneficial for daily use?
I’m facing issues with automation testing because scripts keep breaking after small UI changes, and maintaining them takes too much time and effort. What are the main limitations of automation testing, and how do QA teams handle them?
As a QA expert, I’m doing IoT testing and have a simple problem. My devices work fine in testing but fail in real-world conditions, such as poor network connectivity or multiple connections.
How can I test IoT devices to ensure they work reliably in the real world?