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Annotation Mobile computing and data management.
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Create database designs that scale, meet business requirements, and inherently work toward keeping your data structured and usable in the face of changing business models and software systems. This book is about database design theory. Design theory is the scientific foundation for database design, just as the relational model is the scientific foundation for database technology in general. Databases lie at the heart of so much of what we do in the computing world that negative impacts of poor design can be extraordinarily widespread. This second edition includes greatly expanded coverage of exotic and little understood normal forms such as: essential tuple normal form (ETNF), redundancy free normal form (RFNF), superkey normal form (SKNF), sixth normal form (6NF), and domain key normal form (DKNF). Also included are new appendixes, including one that provides an in-depth look into the crucial notion of data consistency. Sequencing of topics has been improved, and many explanations and examples have been rewritten and clarified based upon the author’s teaching of the content in instructor-led courses. This book aims to be different from other books on design by bridging the gap between the theory of design and the practice of design. The book explains theory in a way that practitioners should be able to understand, and it explains why that theory is of considerable practical importance. Reading this book provides you with an important theoretical grounding on which to do the practical work of database design. Reading the book also helps you in going to and understanding the more academic texts as you build your base of knowledge and expertise. Anyone with a professional interest in database design can benefit from using this book as a stepping-stone toward a more rigorous design approach and more lasting database models. You will: Understand what design theory is and is not Be aware of the two different goals of normalization Know which normal forms are truly significant Apply design theory in practice Be familiar with techniques for dealing with redundancy Understand what consistency is and why it is crucially important .
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Duplikate bzw. Dubletten sind mehrere Datensätze, die das gleiche Realweltobjekt beschreiben, etwa mehrfach erfasste Kunden in einem CRM-System oder unterschiedliche Repräsentationen eines Produkts. Das Auffinden dieser Duplikate ist auch für moderne Computer eine komplexe und zeitintensive Aufgabe. Uwe Draisbach vergleicht zwei der einschlägigen Partitionierungsstrategien, die eine intelligente Auswahl von zu vergleichenden Datensatzpaaren treffen. Daraus entwickelt er ein verallgemeinertes Verfahren und zeigt, dass eine intelligente Auswahl der Datensatzpaare den Aufwand signifikant reduzieren kann, ohne die Qualität der Duplikaterkennung wesentlich zu verringern. Die Arbeit wurde mit dem „Information Quality Best Master Degree Award“ der Deutschen Gesellschaft für Informations- und Datenqualität ausgezeichnet.
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Proceedings of the conference held in Vienna, Austria, April 1993. Papers present current research activities as well as ideas for future directions in data engineering, knowledge engineering, and the synergy of the two.
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