des-semantic-model-design

To design a business-ready semantic model, you specify entities, measures, KPIs, dimensions, relationships, and grain to map Gold data outputs into trusted consumer objects. This approach ensures consistent metrics exposure without writing BI layer implementation code.

Ensuring semantic model security and freshness quality involves defining trust signaling, certification status, and access controls within the model specification. This guarantees that exposed Gold metrics maintain validation-ready standards for safe analytics consumption.

Defining semantic testing and lineage expectations requires specifying evidence packs and metadata requirements within the model specification. This process establishes validation-ready design standards that verify metric transformations against upstream planning artifacts.

Before creating a Phase 16 semantic model specification, you need existing Phase 15 handoff inputs alongside Gold, KPI, contract, and quality context. These upstream planning artifacts provide the required foundation for defining semantic scope and entity relationships.

Yes, you can hand off the semantic model specification to the serving layer design phase once readiness gates pass. This transition produces Phase-Orchestrated Support artifacts including a support plan, evidence pack, and done gate confirmation.

Mapping Gold metrics to semantic dimensions for AI agent serving prevents inconsistent and ambiguous data exposure. This semantic model specification creates a business-friendly layer with defined relationships and grain that safely exposes trusted data.