Barrie Leigh has focused on the design of data sharing systems for three decades, in Europe and the US. He has led the widespread implementation and training of data analysts. He has personally developed large-scale entity models for a wide variety of industries including telecommunications, financial, insurance, manufacturing, transportation, defense, natural resource management and cartography. He has led successful entity analysis for systems solutions of all sizes, from a 30-day start-to-finish circuit provisioning system, to LIFO financial valuation for a $1.6B inventory of raw and semi-finished materials in the steel industry.

Mr. Leigh began his interest in E-R modeling techniques as a systems engineer for IBM in the UK, developing his first E-R diagram in 1971 for an annuity system of Royal Insurance. He was a recognized leader of transactional and database systems design for IBM, in the insurance industry. He evangelized the use of distributed intelligence and distributed database architectures throughout the 1970’s.

As a leading architect with CACI, Mr. Leigh advanced the techniques and practical use of data analysis, with an integrated roadmap of business requirements techniques that included event modeling and business process and use case design. As Vice President of Decision Support Systems for CACI, he carried management and technical leadership responsibility for CACI’s analysis and training services in the US. These same techniques were adopted and promoted in early years by Clive Finkelstein in Australia, carried by Tony Carter and Ian Palmer as they left CACI to found James Martin Associates consulting, and implemented in CACI’s design and development of the original versions of a case tool for Texas Instruments that became known as IEF. Richard Barker (also from CACI) popularized this methodology in Oracle’s CASE*Design tool.

As an independent consultant, Mr. Leigh was selected over Finkelstein, Ken Orr and others to support AT&T and Lucent where he developed and lead AT&T’s analysis training and certification program, for training thousands of business systems analysts. For the Lucent company, he developed the techniques and methods for the systems engineering discipline, and led the development and roll-out of Lucent’s SE training in its software excellence program.

Presently, Mr. Leigh is engaged as an enterprise architect, supporting a multi-disciplinary team that is shaping a unified approach to data sharing, by combining canonical integration messaging models with E-R modeling methods.

Seminar Overview:

The value of entity modeling comes from integration. The results of entity modeling integrate business principles with architecture solutions. The E-R diagram integrates the business terms into a unified taxonomy. The structure of the entities is a fully integrated set of master data patterns. With successful information model integration, our architecture and solutions disaggregate the result into valuable component-requirements for our IT solutions. We mix and match the elements of this business information structure to plan and scope databases, to lay the foundation for class structures, to establish the message content for our application data flows…

And yet, the roadmap to achieve these results can be traveled and illustrated in only half a day. Each step of the way, the entity modeling techniques have built-in diagnostic aids. You don’t need software or case tools to leverage these quality controls. They can all be accomplished with spreadsheets and the right kinds of diagramming. There are diagnostic job-aids to that tell us what is normal and expected from what is eccentric, and perhaps off-track.

This seminar walks through the story of: “Entity Relationship Modeling—fundamentals, diagnostics, quality checks.”

The techniques are foundational, but rarely seen along with the how-to’s and do’s and don’ts. Mr. Leigh’s well-proven storyboard of data requirements analysis will intrigue and challenge the imagination of even the most experienced business information architect. These carefully crafted tips and tricks of entity modeling have turned average data analysts into the Clark Kent’s of our industry.

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Last revised: December 11th, 2006