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

Previous Lesson:

Masterclass: Inclusive Collaboration - how our differences can make the difference with Aaron Hodder
00:58:40
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Next Up:

Strategies to make your automated checks reliable and robust with Peter Bartlett
01:00:58
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From Testing Hell to Testing Well - Adopting Whole Team Approach to Testability with Rob Meaney
01:00:22
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Storytelling & Narratology for Software Testers with Marianne Duijst
01:05:13
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A Software Tester's Guide to Expertise | Vera Gehlen-Baum
01:00:39
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Understanding Mobile Device Fragmentation
01:00:29
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Providing Value to Agile Ceremonies as a Tester with Melissa Tondi
01:06:49
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Introduction to VR Testing with Syed Ali
01:04:34
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Not All Who Wander Are Lost: A Career Experience Report with Hilary Weaver-Robb
00:59:36
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A Tester's Guide to Testing AI Applications with Bill Matthews
01:00:05
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Tips to Improve Collaboration Between Testers and Developers with Franziska Sauerwein & Maaret Pyhäjärvi
01:01:55
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API Mocking and Service Virtualization Explained with Wojciech Bulaty
01:05:25
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Highly Questionable - Being Interview Ready with Ben Kelly
01:01:54
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A Tester's Guide to Blockchain Applications with Rhian Lewis
01:01:04
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Testing Challenges in the Highly Interconnected World of IoT with Bede Ngaruko
01:04:08
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Semantic Spelunking: Exploring Testers and Problems with Damian Synadinos
00:56:28
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Multiplying the Odds with Fiona Charles
00:57:39
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Living the Dream - How You Can Lead Successful Change with Amy Phillips
00:59:19
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Testing Your Requirements with Cucumber, BDD and Example Mapping with Matt Wynne
00:59:54
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Testing Below the Application with Ash Winter
00:52:02
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Truthful Test Estimation with James Bach
01:06:37
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How To Build A Regression Checking Strategy with Mark Winteringham
01:01:43
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Saved by Antifragile by Sami Söderblom
01:00:44
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How to Identify Risk in a Large Code Base with Noah Sussman
00:57:53
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How I Interview Testers with Dan Ashby
01:05:06
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Dealing with Device Fragmentation in Mobile Games Testing with Ru Cindrea
01:00:18
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Mob Testing with Maaret Pyhäjärvi
01:03:49
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The Lone Tester with Jess Ingrassellino
01:00:05
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Where Does All That Testing Time Go? A Masterclass with Michael Bolton
01:06:56
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How to have fun & influence people: Using games to test ideas by Nicola Sedgwick
00:55:46
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Testing Microservices when the stakes are high with Anne-Marie Charrett
00:59:15
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Become The Sherlock Holmes of Software Testing with JeanAnn Harrision
01:30:20
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Continuous Delivery without Test Automation by Maaret Pyhäjärvi
00:55:34
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Getting Started in Security Testing with Dan Billing
01:05:04
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A Practical Approach To Great Test Leadership with Selena Delesie
01:04:38
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Agile Test Leadership and More! with Anna Royzman
00:58:39
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Jump Start Your Performance Testing Effort with Mark Tomlinson
01:03:08
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Description:

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.