Masterclass: How to Test Data Analytics without knowing anything about Data Analytics with Daniel Hunt

Here at Ministry of Testing, we host live monthly online software testing webinars that we lovingly call Masterclasses. All our Masterclasses are presented by software testing masters and are on highly interesting and relevant topics related to software testing and our industry.

In this series, are all the video recordings of our previous Masterclasses for you to enjoy and learn from, permanently!

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Each masterclass is free to attend live, you can see all the upcoming Masterclasses on our events page and the recordings and are made available here shortly after production.

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Masterclass

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!

Takeaways

  • 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.
Daniel Hunt

Daniel has been working as a software tester at a data analytics consultancy after a brief foray into games testing. He has worked on a huge range of different projects across a number of different sectors, each with an analytics component.

Despite being primarily charged with testing the software that houses the data analytics, Daniel likes to find problems wherever they present themselves. This often means testing analytics without deeply understanding it!