Developing high quality data models
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 imp...
| Autor principal: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Burlington, Mass. :
Morgan Kaufmann : Elsevier
2011.
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| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628078206719 |
| Sumario: | 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 |
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| Notas: | Description based upon print version of record. |
| Descripción Física: | 1 online resource (408 p.) |
| Bibliografía: | Includes bibliographical references and index. |
| ISBN: | 9781282954724 9786612954726 9780123751072 |
