What is business logic? Definition and examples for data teams

Business logic refers to the rules and calculations that translate raw data into meaningful metrics for organizational decision-making, and its mismanagement can lead to discrepancies in reported figures, as illustrated by differing revenue reports from finance, marketing, and data warehouses. The problem arises from decentralized implementations of business logic across various tools and platforms, causing metric drift that erodes trust in data reliability. To address these issues, the article suggests centralizing business logic through documentation, version-controlled transformations, and formalized semantic models, which ensures consistent and accurate data interpretation across the organization. This centralization not only mitigates metric inconsistencies but also enhances self-serve analytics and AI adoption by providing a stable reference point for data queries. The piece emphasizes the importance of clear ownership and collaboration between business stakeholders and analytics engineers to maintain and update metric definitions, as demonstrated by successful case studies like Calendly’s Standardized Metric Library. By establishing shared definitions and explicit ownership, organizations can transform data disputes into strategic discussions about leveraging insights for decision-making.