Engineering Agile Big-Data Systems

Kevin Feeney

ISBN 10: 8770220166 / ISBN 13: 9788770220163

Editore: River Publishers, 2018

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nach der Bestellung gedruckt Neuware - Printed after ordering - To be effective, data-intensive systems require extensive ongoing customisation to reflect changing user requirements, organisational policies, and the structure and interpretation of the data they hold. Manual customisation is expensive, time-consuming, and error-prone. In large complex systems, the value of the data can be such that exhaustive testing is necessary before any new feature can be added to the existing design. In most cases, the precise details of requirements, policies and data will change during the lifetime of the system, forcing a choice between expensive modification and continued operation with an inefficient design.Engineering Agile Big-Data Systems outlines an approach to dealing with these problems in software and data engineering, describing a methodology for aligning these processes throughout product lifecycles. It discusses tools which can be used to achieve these goals, and, in a number of case studies, shows how the tools and methodology have been used to improve a variety of academic and business systems.

Codice articolo 9788770220163

Dati bibliografici

• Titolo: Engineering Agile Big-Data Systems
• Editore: River Publishers
• Data di pubblicazione: 2018
• Lingua: Inglese
• ISBN 10: 8770220166
• ISBN 13: 9788770220163
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 240 L x 161 A x 28 P (millimetri) 240 millimetri di larghezza per 161 millimetri di altezza per 28 millimetri di profondità
• Peso: 816 grammi

Descrizione articolo

Riassunto

To be effective, data-intensive systems require extensive ongoing customisation to reflect changing user requirements, organisational policies, and the structure and interpretation of the data they hold. Manual customisation is expensive, time-consuming, and error-prone. In large complex systems, the value of the data can be such that exhaustive testing is necessary before any new feature can be added to the existing design. In most cases, the precise details of requirements, policies and data will change during the lifetime of the system, forcing a choice between expensive modification and continued operation with an inefficient design.Engineering Agile Big-Data Systems outlines an approach to dealing with these problems in software and data engineering, describing a methodology for aligning these processes throughout product lifecycles. It discusses tools which can be used to achieve these goals, and, in a number of case studies, shows how the tools and methodology have been used to improve a variety of academic and business systems.

Informazioni sull?autore

Kevin Feeney, Jim Davies, James Welch