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.

� propos des auteurs

Dr. Kevin Feeney was a senior research fellow in the School of Computer Science and Statistics, Trinity College Dublin, the Information Technology Editor of Seshat Global History Databank, and leader of the ALIGNED research project. He has more than 20 years of experience in developing innovative socio-technical systems in both research and industry, including pioneering distribution of prepaid mobile phone credit through credit card networks and terminals, and developing one of the ﬁrst citizen journalism platforms. He is now CEO of DataChemist.

Prof.JimDaviesisProfessorofSoftwareEngineeringandthedirectorofthe Software Engineering Programme in the Department of Computer Science, University of Oxford. He is a Fellow of Kellogg College. His research interests include the development of automatic generation of systems from re-usable models of structure and functionality, and he is the Principal Investigator on CancerGrid, a consortium to develop open standards for clinical cancer informatics.

Dr.-Ing. Sebastian Hellmann is the head of the Knowledge Integration and LinkedDataTechnologiesgroupinUniversityofLeipzig'sAgileKnowledge Engineering and Semantic Web Group. He is also the executive director and a board member of the non-proﬁt DBpedia Association. He focusses on semantic technology research - often in combination with other areas such as machine learning, databases, and natural language processing

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