Talk Description
This is Data Analytics testing 101! So you've been dumped into testing software containing 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 for you to catch 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? The answer to the last question is a resounding "no"!
Daniel will address all the above questions as he was in a similar situation only 12 months ago! Traversing buzzwords such as machine learning, data science and predictive analytics. Together we'll look at some simple methods, common pitfalls and general approaches that will make sense out of data. There's nothing better than proving that testers can test more than we're supposed to!
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
What you’ll learn
By the end of this masterclass, you'll be able to:
- Describe what Data Analytics is
- List five common processes in data analytics
- Follow a three step plan to get started with Data Analytics
- Discover common pitfalls where data can cause issues
Suggested Content
Topics
Tags
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test-strategies
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data
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test-design
