By Pete Stiglich
Compares enterprise conceptual data models (covering broad domains and shared definitions) with project-level conceptual models (scoped to a specific initiative). It notes that enterprise models are usually developed incrementally and often driven by major programs like ERP, enterprise data warehouses, or SOA. The article argues that building enterprise models is valuable but typically needs alignment with funded enterprise efforts, while projects still benefit from conceptual modeling to clarify scope, integration touchpoints, and common semantics with the larger enterprise view.
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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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