InfoQ Homepage Presentations Too Big to Fail: Running A/B Experiments When You're Betting the Bank
Too Big to Fail: Running A/B Experiments When You're Betting the Bank
Summary
Andrea Burbank discusses the risks, benefits, and lessons from running a single huge experiment with hundreds of moving parts, and with long-term engagement as the metric of success.
Bio
Andrea Burbank works as a data scientist at Pinterest, where she has led A/B testing for the past two years.
About the conference
Software is Changing the World. QCon empowers software development by facilitating the spread of knowledge and innovation in the developer community. A practitioner-driven conference, QCon is designed for technical team leads, architects, engineering directors, and project managers who influence innovation in their teams.
This content is in the QCon Software Development Conference topic
Related Topics:
Sponsored Content
-
Related Editorial
-
Related Sponsors
-
Popular across InfoQ
-
AWS Introduces ECS Managed Instances for Containerized Applications
-
Producing a Better Software Architecture with Residuality Theory
-
GitHub Introduces New Embedding Model to Improve Code Search and Context
-
Google DeepMind Introduces CodeMender, an AI Agent for Automated Code Repair
-
Building Distributed Event-Driven Architectures across Multi-Cloud Boundaries
-
Elena Samuylova on Large Language Model (LLM)-Based Application Evaluation and LLM as a Judge
-