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| Criterion |  Knowledge Modeling Shape-First Modeling |  Operations 8D Problem Solving |  Decision Making Pareto Analysis |  Knowledge Modeling Competency Questions |
|---|---|---|---|---|
Purposedifferent | 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. | For an acute quality or delivery problem, the method structures immediate protection and root cause work together. It keeps the situation stable while the actual cause is investigated cleanly. | In many problem situations, effect is distributed unequally across many causes. A Pareto Analysis separates the few drivers with high leverage from the long remainder and focuses attention on what measurably moves the needle. | Competency Questions translate a domain model into concrete questions that it must be able to answer. The method keeps the model's scope clean and prevents pretty but useless structures. |
Complexitydifferent | Medium | High | Low | Medium |
Timedifferent | Halber Tag pro Domain Slice | 1-6 Wochen | 30-60 min | 2-4 h |
Participantsdifferent | 1-4 | 4-10 | 1-6 | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | 8D Report, Containment Plan, Root Cause Evidence, Corrective Action Plan | Pareto Chart, Top Causes, Focus List | Competency Question Set, Required Concepts, Test Queries, Coverage Matrix |
Tagsno overlap | Knowledge graphValidationSemantic | QualityProblem solvingRoot cause | PrioritizationQualityFocusRoot cause | OntologyKnowledge graphScopeRequirementsSemantic |