A business glossary is a centralized reference that defines business terms, metrics, dimensions, and concepts used across an organization. It ensures that everyone, analysts, executives, engineers, and business users, speaks the same data language.

In analytics-heavy organizations, confusion often comes not from a lack of data but from unclear definitions. A business glossary solves this by documenting what each term means, how it’s calculated, where it comes from, and how it should be used.

A typical business glossary includes:

• Metric definitions (e.g., “Net Revenue”)

• Dimension definitions (e.g., “Customer Segment”)

• Calculation logic

• Data sources

• Ownership and approval status

• Related metrics

From a BI standpoint, the business glossary sits alongside the semantic layer. While the semantic layer enforces logic technically, the glossary explains the logic conceptually.

Business glossaries are especially important in:

• Self-service BI environments

• Regulated industries

• Large organizations with multiple teams

• Embedded analytics products

• AI-driven analytics systems

When AI tools generate insights or answer questions, they rely heavily on glossary definitions to avoid incorrect interpretations.

Modern data catalogs and BI platforms often include built-in glossary features. These allow users to search for terms, see lineage, and understand metric dependencies.

Without a business glossary, organizations experience:

• Conflicting reports

• Loss of trust in dashboards

• Repeated clarification meetings

• Slower decision-making

In summary, a business glossary is not just documentation; it is governance for analytics language, enabling consistency, trust, and scalability across BI systems.