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Engineering Agile Big-Data Systems

Jim Davies (cognitive scientist)

0/5 ( ratings)

To be effective, data-intensive systems require extensive ongoing customization to reflect changing user requirements, organizational policies, and the structure and interpretation of the data they hold. Manual customization 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.

Pages: 250

Format: Hardcover

Publisher: River Publishers

Release: September 30, 2018

ISBN: 8770220166

ISBN 13: 9788770220163

Engineering Agile Big-Data Systems

Jim Davies (cognitive scientist)

0/5 ( ratings)

To be effective, data-intensive systems require extensive ongoing customization to reflect changing user requirements, organizational policies, and the structure and interpretation of the data they hold. Manual customization 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.

Pages: 250

Format: Hardcover

Publisher: River Publishers

Release: September 30, 2018

ISBN: 8770220166

ISBN 13: 9788770220163

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