A requirement engineering model for big data software
A requirement engineering model for big data software
复制标题
大数据软件的需求工程模型
DOI：
10.1109/icbdaa.2017.8284116
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
A. Ghani
中科院分区：
文献类型：
--
作者：
Hamza Altarturi;K. Ng;Mohd Izuan Hafez Ninggal;Azree Nazri;A. Ghani
大多数流行的软件工程方法假设软件系统是从头开始开发的，以捕获业务数据并随后生成报告。如今，海量数据甚至在软件系统开发之前就已经存在了。这些数据也可以在互联网上免费获得，也可以在组织中以孤岛形式呈现。人工智能和计算能力的进步也促使人们需要大数据分析来释放更多商业价值，以支持基于证据的决策。有些业务价值不如其他价值明显，尤其是在孤岛分析数据时。这些价值可以从数据科学家通过数据挖掘过程发现的洞察力中潜在地释放和增强。数据挖掘可能涉及覆盖和合并来自不同来源的数据，以提取数据模式。理想情况下，这些价值最终应该被并入未来的信息系统。为了实现这一点，我们建议软件工程师应该与数据科学家一起得出软件需求。然而，在传统的软件工程过程中，这种协作和商业价值往往被忽视。在本文中，我们提出了一个新的需求工程模型，该模型允许软件工程师和数据科学家在软件需求过程中携手发现这些价值。我们还使用调整后的用例图演示了建议的需求模型如何捕获和表达通过大数据分析释放的业务价值。
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.