des-data-product-definition

A data product specification captures what is inside vs non-scope, primary consumers, supported use cases, and product outputs like dashboards, semantic outputs, APIs, or ML datasets, preventing premature implementation.

Establishing a consumer-backed data product specification with explicit service, trust, access, ownership, and lifecycle expectations prevents shipping disconnected tables-as-products before physical implementation begins.

Create data governance artifacts by generating a data product specification, support plan, evidence pack, revision notes, Done Gate, and phase handoff documents from validated upstream requirements without designing physical schemas or code.

No, data product definition explicitly excludes designing physical schemas, sources, ingestion, transformations, contracts, or code, focusing solely on establishing a bounded product promise and service expectations for downstream phases.

You need a bounded data product promise for dashboards, semantic outputs, APIs, or ML datasets when upstream requirements and prior phase handoffs exist, requiring explicit service and trust expectations before assessing data sources.

Yes, business discovery, functional and non-functional requirements, and KPIs map into a specification defining explicit service, trust, access, ownership, and lifecycle expectations for your data product.