This Masterclass is kindly sponsored by Practitest. Practitest is an end-to-end test management tool. With a unique approach to data organization, it is a common meeting ground for all QA stakeholders and enables full visibility into the testing process and a deeper broader understanding of testing results. It has a vast array of third-party integrations with common bug trackers, automation tools, and robust API for the rest. Learn more about Practitest
This is Data Analytics testing 101! So you've been dumped into testing software that contains some sort of fancy-pants data analytics. The only problem is, you don't/can't/won't(!?) understand it and nobody is going to pay or wait to catch you up to speed. Where do you get started? What can you test about algorithms without any experience or in-depth knowledge? Is it time to give up and start looking for a new job already? Hopefully, there was a resounding No! to that question.
Daniel will address these questions as he was in a similar situation himself only 12 months ago! Traversing such buzzwords as machine learning, data science and predictive analytics we'll take a look at some simple methods, common pitfalls and general approaches that will make sense out of the data. There's nothing better than proving that testers can test more than we're supposed to!
- Learn how to follow the data; not the analytics.
- Discover some common ways that data can cause headaches.
- Find sources of truth wherever you can.
- Confirming correctness is hard but finding flaws is easier.