Writing Effective Business Rules
Morgan Kaufmann Publishers In (Verlag)
978-0-12-385051-5 (ISBN)
Writing Effective Business Rules moves beyond the fundamental dilemma of system design: defining business rules either in natural language, intelligible but often ambiguous, or program code (or rule engine instructions), unambiguous but unintelligible to stakeholders. Designed to meet the needs of business analysts, this book provides an exhaustive analysis of rule types and a set of syntactic templates from which unambiguous natural language rule statements of each type can be generated. A user guide to the SBVR specification, it explains how to develop an appropriate business vocabulary and generate quality rule statements using the appropriate templates and terms from the vocabulary. The resulting rule statements can be reviewed by business stakeholders for relevance and correctness, providing for a high level of confidence in their successful implementation.
Graham C. Witt is an independent consultant with over 30 years of experience in assisting enterprises to acquire relevant and effective IT solutions. His clients include major banks and other financial institutions; businesses in the insurance, utilities, transport and telecommunications sectors; and a wide variety of government agencies. A former guest lecturer on Database Systems at University of Melbourne, he is a frequent presenter at international data management conferences.
Introduction
Chapter 1 – The world of rules
Chapter 2 – How rules work
Chapter 3 – A brief history of rules
Chapter 4 – Types of rules
Chapter 5 – The building blocks of natural language rule statements
Chapter 6 – Fact Models
Chapter 7 – How to write quality natural language rule statements
Chapter 8 – An end-to-end rule management methodology
Chapter 9 – Rule statement templates and subtemplates
| Erscheint lt. Verlag | 15.3.2012 |
|---|---|
| Verlagsort | San Francisco |
| Sprache | englisch |
| Maße | 191 x 235 mm |
| Gewicht | 740 g |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| ISBN-10 | 0-12-385051-7 / 0123850517 |
| ISBN-13 | 978-0-12-385051-5 / 9780123850515 |
| Zustand | Neuware |
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