David Dang, VP of Automated Solutions for Zenergy Technologies, has been a leading figure in the test automation industry for over eighteen years. At Zenergy, David helps organizations build better applications using agile, DevOps, and automation utilizing a mixture of traditional approaches with new technology to make products better, faster, and more reliable. As a technologist, David helps companies transition away from traditional organizational cultural practices, tooling, and software development to modern processes that speed release times while increasing quality software. With his foundation in software development, David can quickly grasp complex IT architectures, critical business functions, and processes as well as cultural dynamics to provide customized automation solutions that provide significant savings for Zenergy’s clients. David is always in high demand as a conference speaker and keynote presenter for his high energy style and humor.
Leveraging Machine Learning & AI for Quality Assurance
Machine learning and artificial intelligence… Seems to be the next “BIG” thing and is expected to bring in over 10 trillion into the economy by 2030. But what is it and what can it do for our industry? We live in an era where technology is constantly at our disposal because of the ease it provides in our everyday lives (like depositing a check through your phone instead of driving all the way to the bank). ML and AI can help make software smarter and more user friendly, such as seeing the same amount deposited every two weeks and notifying the user when a different amount occurs.
We can apply the same concept of smarter software to QA. Join David for an exploration on machine learning and AI including the many benefits each provides. You will dive deeper into three areas where machine learning and AI can be utilized to improve software quality and users’ experiences, such as:
Utilizing machine learning to identify patterns in analytics to provide enhanced user experiences based on their personal interactions with software
Utilizing machine learning to identify patterns based on the completed actions to fix past automation failures. Think, self-healing automation
Optimizing test automation with AI to run only the automation your users want and avoid running automation on the features no one is using.