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| Criterion |  Product Strategy DIBB |  Knowledge Modeling Property Graph Schema Design |  Knowledge Modeling Shape-First Modeling |  Product Discovery Assumption Mapping |
|---|---|---|---|---|
Purposedifferent | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. | Property Graph Schema Design turns business and technical requirements into a robust graph schema. It fits when query patterns, constraints, and migrations need to be thought about together. | Shape-First Modeling defines data quality through shapes before implementation or integration frays at the edges. The approach fits when validation and data contracts should be part of the design from the start. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. |
Complexitydifferent | Low | Medium | Medium | Medium |
Timedifferent | 1-2 h | 4-8 h initial, dann iterativ | Halber Tag pro Domain Slice | 45-60 min |
Participantsdifferent | 2-8 | 1-6 | 1-4 | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | Schema Diagram, Node and Relationship Catalog, Index Plan, Migration Scripts, Sample Queries | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Assumption map, Test backlog, Risk ranking |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | Knowledge graphModelingSemantic | Knowledge graphValidationSemantic | AssumptionsRiskExperimentsValidation |