Master Data Management & Enterprise Engineering
暫譯: 主數據管理與企業工程

It is in the context of maturity that one needs to read the book – Master Data Management and Enterprise Engineering by Dr. M. Naoulo. The world of technology has several related yet distinct approaches – Martin’s and Finklestein’s information engineering, Ted Codd’s relational technology, Inmon’s data warehouse, and others. This book takes these approaches and others and does two important things – it blends them together and it takes the bodies of thought and turns them into an engineering approach. As such this book is another important step in the evolution of computer science. This is a next step in the maturation of computer science. I recommend it to any serious student of computer science or to any serious practitioner. =========== W.H. (Bill) Inmon. May 21, 2012. =========== The book establishes the Fundamentals of design, modeling, architecture, and management of Master, Transactional, and Process Data and the Principles of Enterprise Engineering. The book comprises innovative techniques and elegant approach and design to address: > Master Data Management thru grouping and classifying the Master Data in an innovative way that can be implemented across the Enterprise Data Architecture: Central Data Repository and Business and Enterprise Intelligence (BI & EI) Data Marts. This data classification is based on the questions: Why, How, Who, What, Where and When. > Separating the Master Data, Transactional Data, and Process Data. This separation enables the easiness in dealing with MDM, BI, and EI. The separation approach enormously facilitates the mapping and propagation between the Central Data Repository and the Business and Enterprise Data Marts. >The basics and techniques of the design of the Enterprise Engineering Model. This model supports the Transactional Systems, Business Intelligence, Business Process Management, Enterprise Intelligence, and Enterprise Engineering. > Synchronization and Integration of Master, Transactional, and Process Data across the enterprise: Legacy Systems, Central Data Repository, and Business and Intelligence Data Marts. > Assessing the different Enterprise Data Architectures. The first part encompasses the Enterprise Data Framework and its new Modeling Techniques. The Enterprise Data Framework illustrates and depicts the Data Architecture across the enterprise covering the integration and consolidation of the data of the Legacy Systems in a Central Data Repository and the propagation of this data into the Business and Enterprise Intelligence Data Marts. The Enterprise Engineering Model presents a clear and concise illustration depicting the Operational aspects of the Enterprise and their relations to the Enterprise’s needs. It includes: > Master Data representing the main objects of an enterprise, > Transactional Data detailing the results of transactions occurring in an enterprise, and > Process Data capturing the data pertinent to the activities of the functioning of an enterprise. The second part encompasses the Enterprise Engineering Framework, Methodology, Guidelines, Deliverables, and Techniques. It bestows the blueprint of the functioning of enterprises. This part details the basics of Enterprise Engineering and its implementation thru the processing of the Enterprise Engineering Model. It provides the cost data (materiel cost, labor cost, time) reflecting the functioning of the Enterprise and point out the efficiency, performance, strengths, and weaknesses of its operation. Detailed Case Studies are presented supporting the theoretical aspect of Enterprise Engineering. These Case Studies provide clear and practical hands-on exercises reflecting the functioning of the Enterprises and illustrating the implementation of Enterprise Engineering.