Data Design in software development has always been a challenge. The heterogeneous nature of data has always demanded designers to follow engineered design practices to model data. One such model is object-oriented data which later led to object-relational data, which then became a more powerful data model for high-end applications. Nowadays, as we have bigdata in every applications, it has become a mandate for designers to give highest priority in handling well-defined data. Hence we have attempted in this book to propose metrics for object-relational data that would help data designers to come up with better data models. We have defined six software metrics and categorized them to Structural, Functional and Storage metrics, where all metrics are focused on the design of OR Data. We have validated these metrics using two case-studies. These studies would help software architects to boldly venture into adopting these metrics into their object-relational data modeling.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data Design in software development has always been a challenge. The heterogeneous nature of data has always demanded designers to follow engineered design practices to model data. One such model is object-oriented data which later led to object-relational data, which then became a more powerful data model for high-end applications. Nowadays, as we have bigdata in every applications, it has become a mandate for designers to give highest priority in handling well-defined data. Hence we have attempted in this book to propose metrics for object-relational data that would help data designers to come up with better data models. We have defined six software metrics and categorized them to Structural, Functional and Storage metrics, where all metrics are focused on the design of OR Data. We have validated these metrics using two case-studies. These studies would help software architects to boldly venture into adopting these metrics into their object-relational data modeling. 216 pp. Englisch. N° de réf. du vendeur 9786139451395
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Selwyn JustusDr. S. Justus, Associate Professor, VIT Chennai India, is working in the areas of Software/Knowledge Engineering, Object-Relational Data Model. He is the co-founder of INCLEFS Software Consultancy company, working on ind. N° de réf. du vendeur 280827228
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Taschenbuch. Etat : Neu. Software Metrics for Object-Relational Data Modeling | Justus Selwyn (u. a.) | Taschenbuch | 216 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786139451395 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. N° de réf. du vendeur 115846967
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Data Design in software development has always been a challenge. The heterogeneous nature of data has always demanded designers to follow engineered design practices to model data. One such model is object-oriented data which later led to object-relational data, which then became a more powerful data model for high-end applications. Nowadays, as we have bigdata in every applications, it has become a mandate for designers to give highest priority in handling well-defined data. Hence we have attempted in this book to propose metrics for object-relational data that would help data designers to come up with better data models. We have defined six software metrics and categorized them to Structural, Functional and Storage metrics, where all metrics are focused on the design of OR Data. We have validated these metrics using two case-studies. These studies would help software architects to boldly venture into adopting these metrics into their object-relational data modeling.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 216 pp. Englisch. N° de réf. du vendeur 9786139451395
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data Design in software development has always been a challenge. The heterogeneous nature of data has always demanded designers to follow engineered design practices to model data. One such model is object-oriented data which later led to object-relational data, which then became a more powerful data model for high-end applications. Nowadays, as we have bigdata in every applications, it has become a mandate for designers to give highest priority in handling well-defined data. Hence we have attempted in this book to propose metrics for object-relational data that would help data designers to come up with better data models. We have defined six software metrics and categorized them to Structural, Functional and Storage metrics, where all metrics are focused on the design of OR Data. We have validated these metrics using two case-studies. These studies would help software architects to boldly venture into adopting these metrics into their object-relational data modeling. N° de réf. du vendeur 9786139451395
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Etat : Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Data Design in software development has always been a challenge. The heterogeneous nature of data has always demanded designers to follow engineered design practices to model data. One such model is object-oriented data which later led to object-relational data, which then became a more powerful data model for high-end applications. Nowadays, as we have bigdata in every applications, it has become a mandate for designers to give highest priority in handling well-defined data. Hence we have attempted in this book to propose metrics for object-relational data that would help data designers to come up with better data models. We have defined six software metrics and categorized them to Structural, Functional and Storage metrics, where all metrics are focused on the design of OR Data. We have validated these metrics using two case-studies. These studies would help software architects to boldly venture into adopting these metrics into their object-relational data modeling. N° de réf. du vendeur 34027811/1
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