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| Criterion |  Knowledge Modeling Shape-First Modeling |  Decision Making Pareto Analysis |  Operations 5 Whys |
|---|---|---|---|
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. | 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. | For a single, hard-to-explain deviation, the method exposes the causal chain behind the visible symptom. It keeps the cause open until a controllable condition emerges instead of a mere description. |
Complexitydifferent | Medium | Low | Low |
Timedifferent | Halber Tag pro Domain Slice | 30-60 min | 15-30 min |
Participantsdifferent | 1-4 | 1-6 | 2-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop |
Outputdifferent | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Pareto Chart, Top Causes, Focus List | Root cause notes, Countermeasures |
Tagsno overlap | Knowledge graphValidationSemantic | PrioritizationQualityFocusRoot cause | Root causeIncidentLeanProblem solving |
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