A data science model is a statistical black box; testing it requires an understanding of mathematical techniques like algorithms, randomness, and statistics. To validate data science models you ...

Hypothesis testing relies exclusively on data and doesn’t provide a comprehensive understanding of the subject being studied. Additionally, the accuracy of the results depends on the quality of ...

Big data testing plays a massive role in helping companies identify defects in real time, reduce storage costs, make smarter decisions, manage client expectations and implement new strategies.

Data migration testing ensures that all your data sets and system integrity are maintained when they’re transferred to a different host. Depending on the size of your organization and the work ...

We look at backup testing – why you should do it, what you should do, when you should do it, and how, with a view to the ways in which it will be made easier by forthcoming developments in ...