Engineering Agile Big-Data Systems
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, th...
Сохранить в:
| Главные авторы: | , , |
|---|---|
| Формат: | Online |
| Язык: | английский |
| Опубликовано: |
Taylor & Francis
2022
|
| Предметы: | |
| Online-ссылка: | ONIX_20221128_9781000795868_33 |
| Метки: |
Нет меток, Требуется 1-ая метка записи!
|
| _version_ | 1869527556217110528 |
|---|---|
| author | Feeney, Kevin Davies, Jim Welch, James |
| author_browse | Davies, Jim Feeney, Kevin Welch, James |
| author_facet | Feeney, Kevin Davies, Jim Welch, James |
| author_sort | Feeney, Kevin |
| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-94314 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Taylor & Francis |
| publisherStr | Taylor & Francis |
| record_format | ojs |
| spelling | doab-20.500.12854ir-943142025-05-08T12:58:50Z Engineering Agile Big-Data Systems Feeney, Kevin Davies, Jim Welch, James Computer programming / software engineering Data mining 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. 2022-11-29T04:03:37Z 2022-11-29T04:03:37Z 2022-11-28T16:04:14Z 2018 book ONIX_20221128_9781000795868_33 https://library.oapen.org/handle/20.500.12657/59749 9781000795868 9781003338123 9788770220163 https://directory.doabooks.org/handle/20.500.12854/94314 eng open access image/jpeg image/jpeg image/jpeg n/a n/a n/a https://library.oapen.org/bitstream/20.500.12657/59749/1/9781000795868.pdf https://library.oapen.org/bitstream/20.500.12657/59749/1/9781000795868.pdf https://library.oapen.org/bitstream/20.500.12657/59749/1/9781000795868.pdf Taylor & Francis River Publishers 10.1201/9781003338123 10.1201/9781003338123 fa69b019-f4ee-4979-8d42-c6b6c476b5f0 European Commission 3983007a-5726-4f1e-b9df-3fbc771f2916 9781000795868 9781003338123 9788770220163 EU collection River Publishers 302 [...] open access |
| spellingShingle | Computer programming / software engineering Data mining Feeney, Kevin Davies, Jim Welch, James Engineering Agile Big-Data Systems |
| title | Engineering Agile Big-Data Systems |
| title_full | Engineering Agile Big-Data Systems |
| title_fullStr | Engineering Agile Big-Data Systems |
| title_full_unstemmed | Engineering Agile Big-Data Systems |
| title_short | Engineering Agile Big-Data Systems |
| title_sort | engineering agile big data systems |
| topic | Computer programming / software engineering Data mining |
| topic_facet | Computer programming / software engineering Data mining |
| url | ONIX_20221128_9781000795868_33 |
| work_keys_str_mv | AT feeneykevin engineeringagilebigdatasystems AT daviesjim engineeringagilebigdatasystems AT welchjames engineeringagilebigdatasystems |