Automated Experiment Analysis - Making experimental analysis scalable

This post introduces the Automated Experiment Analysis platform, a data product that standardizes and automates the statistical analysis of experiments (A/B tests). It addresses inefficiencies and quality control issues of manual analysis by implementing a metrics glossary, automated data pipelines (bronze, silver, gold datasets), and a "Decision Engine" for statistical analysis. Results are visualized via embedded Power BI. Key technical components include Azure Data Lake for metadata storage, Spark for ETL jobs on Databricks, a Python package "Decision Engine" for statistical tests, and embedded Power BI for visualization. Future plans include a centralized metric store, end-to-end experiment guide rails, and a more comprehensive analysis toolbox.