By Zongmin Ma
Accumulating and featuring the most recent study and improvement effects from the prime researchers within the box of business database modeling, Database Modeling for commercial facts administration: rising applied sciences and functions presents a unmarried checklist of present examine and useful functions in business database modeling. This ebook discusses the key facets of databases for undefined: facts modeling, database types, and database purposes in info systems.Readers of Database Modeling for business information administration: rising applied sciences and purposes will achieve a whole figuring out of the notions, strategies, and techniques regarding the learn and advancements of business database modeling, that allows you to function either a place to begin and a reference for his or her examine and advancements
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Extra resources for Database Modeling for Industrial Data Management: Emerging Technologies and Applications
Hua, Y. (1998). A fuzzy knowledge base to support routine engineering design. Fuzzy Sets and Systems, 98, 267-278. , & Fromherz, M. P. J. (1997). Design optimization with uncertain application knowledge. In Proceedings of the 10th International Conference on Industrial and Engineering Application of Artificial Intelligence and Expert Systems, Atlanta, GA (pp. 421-430). Gordon and Breach Science Publishers. , & Evans, G. W. (1986). Fuzzy concepts in production management research: A review. International Journal of Production Research, 24(1), 129-147.
In constraint databases, complex spatial and/or temporal data can be modeled. In particular, constraint databases can handle a wealth of constraints in engineering design. Conclusion Manufacturing enterprises obtain increasing product varieties and products with lower price, high quality and shorter lead time by using enterprise information systems. The enterprise information systems have become the nerve center of current computer-based manufacturing enterprises. Manufacturing engineering is typically a data- and knowledge-intensive application area and engineering information modeling is hereby one of the crucial tasks to implement engineering information systems.
So EER and UML should be used to design EXPRESS data model conceptually, and then such EER and UML data models can be translated into EXPRESS data model. It should be pointed out that, however, for Web-based engineering applications, XML should be used for conceptual data modeling. Just like EXPRESS, XML is not a graphical schema language, either. EER and UML can be used to design XML data model conceptually, and then such EER and UML data models can be translated into XML data model. That multiple graphical data models can be employed facilitates the designers with different background to design their conceptual models easily by using one of the graphical data models with which they are familiar.