Analytics can sometimes be a tricky topic, especially in a world of big data. This short video identifies problems that can become highlighted by Quality Assurance Analytics; Broken processes, skills gaps and poor performance.
Analysing data is only useful when the results are interpreted into insights that can be acted upon, otherwise its just a bunch of numbers and lines. There is a process for using quality assurance analytics and it follows the 5 Steps outlined below.
1. Gather data.
2. Run multiple reports.
3. Analyse the results.
4. Gain insights.
5. Take action from the insights.
Can QA Analytics outline other problems?
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Video courtesy of planetvidd.com
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