A requirement engineering model for big data software
Most prevailing software engineering methodologies assume that software systems are developed from scratch to capture business data and subsequently generate reports. Nowadays, massive data may exist even before software systems are developed. These data may also be freely available on Internet or m...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2017
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| Online Access: | http://psasir.upm.edu.my/id/eprint/59507/ http://psasir.upm.edu.my/id/eprint/59507/1/A%20requirement%20engineering%20model%20for%20big%20data%20software.pdf |
| _version_ | 1848853940361232384 |
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| author | Altarturi, Hamza Hussein Ng, Keng Yap Ninggal, Mohd Izuan Hafez Ahmad Nazri, Azree Shahrel Abd Ghani, Abdul Azim |
| author_facet | Altarturi, Hamza Hussein Ng, Keng Yap Ninggal, Mohd Izuan Hafez Ahmad Nazri, Azree Shahrel Abd Ghani, Abdul Azim |
| author_sort | Altarturi, Hamza Hussein |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Most prevailing software engineering methodologies assume that software systems are developed from scratch to capture business data and subsequently generate reports. Nowadays, massive data may exist even before software systems are developed. These data may also be freely available on Internet or may present in silos in organizations. The advancement in artificial intelligence and computing power has also prompted the need for big data analytics to unleash more business values to support evidence-based decisions. Some business values are less evident than others, especially when data are analyzed in silos. These values could be potentially unleashed and augmented from the insights discovered by data scientists through data mining process. Data mining may involve overlaying and merging data from different sources to extract data patterns. Ideally, these values should be eventually incorporated into the information systems to be. To realize this, we propose that software engineers ought to elicit software requirements together with data scientists. However, in the traditional software engineering process, such collaboration and business values are usually neglected. In this paper, we present a new requirement engineering model that allows software engineers and data scientists to discover these values hand in hand as part of software requirement process. We also demonstrate how the proposed requirement model captures and expresses business values that unleashed through big data analytics using an adapted use case diagram. |
| first_indexed | 2025-11-15T11:01:57Z |
| format | Conference or Workshop Item |
| id | upm-59507 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:01:57Z |
| publishDate | 2017 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-595072018-03-07T07:19:15Z http://psasir.upm.edu.my/id/eprint/59507/ A requirement engineering model for big data software Altarturi, Hamza Hussein Ng, Keng Yap Ninggal, Mohd Izuan Hafez Ahmad Nazri, Azree Shahrel Abd Ghani, Abdul Azim Most prevailing software engineering methodologies assume that software systems are developed from scratch to capture business data and subsequently generate reports. Nowadays, massive data may exist even before software systems are developed. These data may also be freely available on Internet or may present in silos in organizations. The advancement in artificial intelligence and computing power has also prompted the need for big data analytics to unleash more business values to support evidence-based decisions. Some business values are less evident than others, especially when data are analyzed in silos. These values could be potentially unleashed and augmented from the insights discovered by data scientists through data mining process. Data mining may involve overlaying and merging data from different sources to extract data patterns. Ideally, these values should be eventually incorporated into the information systems to be. To realize this, we propose that software engineers ought to elicit software requirements together with data scientists. However, in the traditional software engineering process, such collaboration and business values are usually neglected. In this paper, we present a new requirement engineering model that allows software engineers and data scientists to discover these values hand in hand as part of software requirement process. We also demonstrate how the proposed requirement model captures and expresses business values that unleashed through big data analytics using an adapted use case diagram. IEEE 2017 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/59507/1/A%20requirement%20engineering%20model%20for%20big%20data%20software.pdf Altarturi, Hamza Hussein and Ng, Keng Yap and Ninggal, Mohd Izuan Hafez and Ahmad Nazri, Azree Shahrel and Abd Ghani, Abdul Azim (2017) A requirement engineering model for big data software. In: 2017 IEEE Conference on Big Data and Analytics (ICBDA 2017), 16-17 Nov. 2017, Riverside Majestic Hotel, Kuching, Sarawak. (pp. 111-117). 10.1109/ICBDAA.2017.8284116 |
| spellingShingle | Altarturi, Hamza Hussein Ng, Keng Yap Ninggal, Mohd Izuan Hafez Ahmad Nazri, Azree Shahrel Abd Ghani, Abdul Azim A requirement engineering model for big data software |
| title | A requirement engineering model for big data software |
| title_full | A requirement engineering model for big data software |
| title_fullStr | A requirement engineering model for big data software |
| title_full_unstemmed | A requirement engineering model for big data software |
| title_short | A requirement engineering model for big data software |
| title_sort | requirement engineering model for big data software |
| url | http://psasir.upm.edu.my/id/eprint/59507/ http://psasir.upm.edu.my/id/eprint/59507/ http://psasir.upm.edu.my/id/eprint/59507/1/A%20requirement%20engineering%20model%20for%20big%20data%20software.pdf |