We are excited to announce that we have just released BigFlow 1.0 as open source. It’s a Python framework for big data processing on the Google Cloud Platform.
Developing our own A/B testing platform from scratch came with many lessons during the process. Our platform was built for people who differ vastly in terms of statistical knowledge, also for those who are not familiar with statistics at all. So the main challenge wasn’t technical implementation. The hardest thing was (and still is) developing good practices and spreading them among our users. We want to share some of our current knowledge that we think is crucial for A/B testing at scale. From this article, you will get to know about calculating sample size, what it means and what benefits it provides for you and your organization.
Bartek is a software engineer who works on the Allegro experimentation platform. He is allergic to the status quo.