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  • 1
    Online-Ressource
    Online-Ressource
    Burlington, Mass. :Morgan Kaufmann :
    UID:
    almafu_9960073635802883
    Umfang: 1 online resource (408 p.)
    Ausgabe: 1st edition
    ISBN: 9786612954726 , 9781282954724 , 1282954725 , 9780123751072 , 0123751071
    Inhalt: A multitude of problems is likely to arise when developing data models. With dozens of attributes and millions of rows, data modelers are always in danger of inconsistency and inaccuracy. The development of the data model itself could result in difficulties presenting accurate data. The need to improve data models begins with getting it right in the first place. Using real-world examples, Developing High Quality Data Models walks the reader through identifying a number of data modeling principles and analysis techniques that enable the development of data models that bo
    Anmerkung: Description based upon print version of record. , pt. 1. Motivations and notations -- pt. 2. General principles for data models -- pt. 3. An ontological framework for consistent data models -- pt. 4. The HQDM framework schema. , English
    Weitere Ausg.: ISBN 9780123751065
    Weitere Ausg.: ISBN 0123751063
    Sprache: Englisch
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 2
    Online-Ressource
    Online-Ressource
    Amsterdam : Elsevier, Morgan Kaufmann
    UID:
    gbv_165131991X
    Umfang: Online Ressource (xvii, 389 p.)
    ISBN: 9780123751065 , 0123751063 , 9780123751072 , 0123751071 , 1282954725 , 9781282954724
    Inhalt: Chapter 1: What are Data Models For? Chapter 2: Different Sorts of Data Models Chapter 3: Languages and Notations for Data and Data Models Chapter 4: Layout of Data Models Chapter 5: Reviewing and Improving Data Models Chapter 6: High Quality Data Models Chapter 7: Principles for Data Models Chapter 8: A Generic Framework for a Changing World Chapter 9: Integration of Data Models Chapter 10: Future Directions
    Inhalt: A multitude of problems is likely to arise when developing data models. With dozens of attributes and millions of rows, data modelers are always in danger of inconsistency and inaccuracy. The development of the data model itself could result in difficulties presenting accurate data. The need to improve data models begins with getting it right in the first place. Using real-world examples, Developing High Quality Data Models walks the reader through identifying a number of data modeling principles and analysis techniques that enable the development of data models that both meet business requirements and have a consistent basis. The reader is presented with a variety of generic data model patterns that both exemplify the principles and techniques discussed and build upon one another to give a powerful and integrated generic data model. This model has wide applicability across many disciplines in government and industry, including but not limited to energy exploration, healthcare, telecommunications, transportation, military defense, transportation, and more. * Uses a number of common data model patterns to explain how to develop data models over a wide scope in a way that is consistent and of high quality *Offers generic data model templates that are reusable in many applications and are fundamental for developing more specific templates *Develops ideas for creating consistent approaches to high quality data models
    Anmerkung: Includes bibliographical references and index. - Description based on print version record , Chapter 1: What are Data Models For? Chapter 2: Different Sorts of Data Models Chapter 3: Languages and Notations for Data and Data Models Chapter 4: Layout of Data Models Chapter 5: Reviewing and Improving Data Models Chapter 6: High Quality Data Models Chapter 7: Principles for Data Models Chapter 8: A Generic Framework for a Changing World Chapter 9: Integration of Data Models Chapter 10: Future Directions. , A multitude of problems is likely to arise when developing data models. With dozens of attributes and millions of rows, data modelers are always in danger of inconsistency and inaccuracy. The development of the data model itself could result in difficulties presenting accurate data. The need to improve data models begins with getting it right in the first place. Using real-world examples, Developing High Quality Data Models walks the reader through identifying a number of data modeling principles and analysis techniques that enable the development of data models that both meet business requirements and have a consistent basis. The reader is presented with a variety of generic data model patterns that both exemplify the principles and techniques discussed and build upon one another to give a powerful and integrated generic data model. This model has wide applicability across many disciplines in government and industry, including but not limited to energy exploration, healthcare, telecommunications, transportation, military defense, transportation, and more. * Uses a number of common data model patterns to explain how to develop data models over a wide scope in a way that is consistent and of high quality *Offers generic data model templates that are reusable in many applications and are fundamental for developing more specific templates *Develops ideas for creating consistent approaches to high quality data models
    Weitere Ausg.: ISBN 9780123751065
    Weitere Ausg.: ISBN 0123751063
    Weitere Ausg.: ISBN 0123751071
    Weitere Ausg.: Erscheint auch als Druck-Ausgabe West, Matthew, 1953 - Developing high quality data models Amsterdam : Elsevier, Morgan Kaufmann, 2011 ISBN 0123751063
    Weitere Ausg.: ISBN 9780123751065
    Sprache: Englisch
    Fachgebiete: Informatik
    RVK:
    Schlagwort(e): Datenmodell ; Datenstruktur
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
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