What is business logic? Definition and examples for data teams

This post defines business logic as the rules and calculations that translate raw data into organizational decision-making metrics. It differentiates business logic from business rules, explains why scattered logic erodes trust and complicates AI adoption, and outlines a progressive approach to centralization: 1. Document and endorse datasets. 2. Move logic into version-controlled transformations (e.g., dbt models). 3. Formalize with semantic models. It highlights Hex's capabilities in semantic model sync and its Semantic Model Agent for building and editing definitions, and Context Studio for surfacing governance gaps. The post also emphasizes clear ownership of metric meaning vs. implementation.