By Pete Stiglich
Outlines common approaches for transforming a conceptual data model into a logical data model. One approach expands the CDM by identifying additional entities, fully attributizing them with business nomenclature, resolving many‑to‑many relationships, formalizing keys, handling subtypes, and applying abstraction and normalization. Another approach keeps the LDM closer to an attributized CDM and postpones some resolutions until the physical model, allowing multiple physical manifestations (OLTP vs. dimensional) while maintaining metadata relationships. It emphasizes disciplined steps to avoid semantic drift.
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Pete Stiglich: Trusted Expert in Data Architecture & Modeling
Pete has over 30 years of data architecture, data management, and analytics experience, most of that time as a consultant in industries such as government, finance, healthcare, insurance, and more. He is an industry thought leader in data architecture and data modeling and has developed and taught many courses on these topics. Pete enjoys helping clients solve complex data problems, leveraging proven approaches such as “Modeling the business before modeling the solution” which provides a benefit to clients that many IT professionals miss.
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