Engineering Agile Big-Data Systems (open source)

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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, 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.

Kevin Feeney, Trinity College Dublin, Ireland
Jim Davies, Oxford University, United Kingdom
James Welch, Oxford University, United Kingdom
Sebastian Hellmann, University of Leipzig, Germany
Christian Dirschl, Wolters Kluwer, Germany
Andreas Koller, Semantic Web Company, Austria
Pieter Francois, Oxford University, United Kingdom
Arkadiusz Marciniak, Adam Mickiewicz University, Poland

ISBN: 9788770220163