This company, in conjunction with clients, designs data and process models to support strategic planning, requirements analysis, data warehouse design, and data quality efforts. It has supported a wide range of industries, both in the United States and abroad, such as financial services, oil and gas exploration and refining, the intelligence community, shipping, and many others. Founder David Hay has written many books on data architecture and modeling techniques.

Assisting organizations (both private and government) with data architecture, methodology, data modeling, and data warehouse design. In particular, I am interested in assisting clients with understanding and capturing the way their organizations use language both for communicating among themselves and establishing systems which communicate equivalently.Provide semantic and conceptual data modeling support to strategic planning, governance, and other requirements analysis projects. Supported a wide variety of industries, including both upstream and downstream petroleum, clinical research, financial services, movie and television production, and others. Many articles on data management, modeling, methodologies, and other subjects available at http://davehay.articles.com. (You have to register, but it's free!)

"Requirements Analysis: From Business Views to Architecture" is a compendium of thirty years' of techniques for defining the nature of an organization, to provide a context for specifying requirements for new systems. The techniques are organized in terms of Mr. Hay's version of John Zachman's "Framework for Information Architecture". It's premise is that the analyst's job is to take a collection of "business owners' views" and integrate them into a simpler, more coherent "architect's view". The views of course are of data (what), activities (how), people and organizations (who), events and timing (when), and motivation (why). This is a unique approach to requirements analysis: instead of asking people, "OK, what would you like a new system to do?" we ask "What do you do?" "What data do you require to do it?" And so forth. Eventually, we ask, "What is your biggest problem?" But know we know how to put it in context.Translated into Chinese.Recently re-published in paperback.

Wrote articles. Gave presentations at international conferences and local chapters.

The first book, "Enterprise Model Patterns: Describing the World" is a proper successor to "Data Model Patterns: Conventions of Thought". It presents the patterns in terms of "levels of abstraction".Level 1 models generic concepts: people and organizations, physical assets, etc.; Level 2 provides more concrete views of functional areas: facilities management, contracts, etc.; Level 3 is a representative sample of the difficult parts of modeling five particular industries. The idea is that for any company, the more general models work for most of its practices. A few particular bits, though, require special attention.The second book, published in 2011, is "UML and Data Modeling: a Reconciliation". This is an attempt to modify UML slightly so that it can be used for business-oriented conceptual modeling. It shows data modelers how UML can be used to create a conceptual data model, and UML modelers how to extend their understanding of the nature of the notation..In addition, there is considerable guidance about how to produce a high quality (precise, accurate, accessible) data model, regardless of the notation chosen.The third book, published in 2018, is called "Achieving Buzzword Compliance: Data Architecture Language and Vocabulary". The Data Architecture field is rife with "buzzwords": technical terms that have become “fashionable”. Some of these began with very specific, specialized, meanings – but as their use spread, they lost the precision of their technical definitions and became, well, “buzzwords”. (Consider: “logical” and “conceptual” data models.) We have to deal not only with “entity relationship model” and “object role modeling”, but also with "dimensional modeling", “the Semantic Web”, and “NoSQL”, among many others. Oh, and can anyone define “canonical model”?It turns out that data industry is beginning to converge on these and related terms. But it’s not quite done yet. This book is a humble attempt to complete the process:

"Data Model Patterns: A Metadata Map" is a comprehensive schema of metadata, organized in terms of Mr. Hay's version of John Zachman's "Framework for Information Architecture". The "business owner's view" is concerned with semantics, business functions, current business processes, goals and objectives, and so forth. The "architect's view" is concerned with conceptual (architectural) entity/relationship models, "essential" data flow diagrams, strategies and tactics, and so forth.The "designer's view" is concerned with databases, computer programs, user interfaces, control networks, and so forth.The metadata for each of these "cells" is comprehensive in its own right, but is intricately connected with the metadata in each other cell. This is all presented in the book.If you are going to create (or buy, for that matter) a metadata repository, you can use this as a roadmap.Available in both print and electronic versions.

"Data Model Patterns: Conventions of Thought" was the ground-breaking book that introduced the world to patterns in data modeling. Its set of standard models of standard business situations still is being used. While "Enterprise Model Patterns: Describing the World" is more comprehensive (reflecting 15 years of additional experience), the original book remains a good place to start for a novice modeler. (Translated into Brazilian Portuguese.)Translated into Portuguese in Brazil.(It has recently been republished in paperback.)