By Pete Stiglich
A practitioner’s “wish list” for what modern data-modeling tools should do better: support collaboration, manage definitions and metadata as first‑class artifacts, and help teams handle change without breaking downstream consumers. The article emphasizes traceability (requirements → model → implementation), stronger versioning and impact analysis, and better support for enterprise standards such as naming, domains, and reusable patterns. The overall theme is reducing friction between business and IT while improving governance, quality, and maintainability.
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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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