Curriculum at a glanceSection 1 — Introduction and FoundationEstablish a foundation for advanced data modeling by applying cross-enterprise, model-driven analysis techniques to identify baseline and complex data patterns across business domains. Section 2 — Abstraction & GeneralizationLearn how to abstract and generalize data structures by managing entity hierarchies, metadata transitions, coupling and cohesion, and distinguishing between static and dynamic entity behaviors. Section 3 — Advanced Data PatternsExplore advanced data modeling patterns including subtypes, recursive structures, rules-based entities, state transitions, and meta-patterns used to represent complex, real-world business scenarios. Section 4 — Enterprise Requirements AnalysisApply enterprise-level analysis techniques to sequence requirements, analyze metadata for abstraction opportunities, define cohesive subject areas, and design flexible, extensible logical data models. Section 5 — Discovering Business KnowledgeMaster professional discovery techniques to uncover meaningful business knowledge, avoid superficial requirements gathering, and ensure analysis drives real insight rather than simple order taking. Section 6 — Case StudyAnalyze a complex business scenario and develop a detailed logical data model using advanced patterns, gaining hands-on experience applying techniques directly transferable to real organizational contexts. Section 7 — Best Practices and Practical TipsReinforce learning through best practices covering conceptual versus logical modeling, logical-to-physical transformation, business rule discovery, enterprise reference models, and real-world application guidance. |
|
