des-lineage-metadata-design

Data lineage and metadata design defines what data means, how it was produced, and how it stays trustworthy across business, technical, operational, and reference layers. It produces a specification with evidence mapping for downstream consumers, governance, and operators.

To design lineage and metadata specifications, use existing dataset, contract, transformation, quality, semantic, and serving artifacts as inputs. The process generates a Phase 18 support plan, evidence pack, artifact revision report, and a governance-ready handoff.

The best way to map metadata decisions to evidence is through evidence-driven validation that includes HALT-driven risk handling. This approach specifies dataset, transformation, semantic, and serving lineage while linking key governance decisions directly to supporting evidence.

Yes, you need Phase 17 Serving Layer Specification and the Phase 17 to 18 handoff available before starting. Lineage design requires existing planning artifacts including dataset, contract, transformation, quality, and semantic artifacts to validate readiness.

No, this lineage design approach does not implement catalog tools or lineage pipelines. It focuses strictly on designing and validating lineage and metadata requirements to produce a governance-ready specification and support-plan deliverables.

You should capture metadata across business, technical, operational, and reference layers. The design process defines metadata scope and inventory to explicitly determine what metadata to capture and what to exclude for your specific data products.