大数据系统开发:一个全球外包公司的嵌入式案例研究

Hong-Mei Chen, R. Kazman, Serge Haziyev, Olha Hrytsay
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引用次数: 38

摘要

大数据系统的开发与小型(传统的、结构化的)数据系统的开发有很大的不同。2014年底,大数据部署仍然稀缺,失败比比皆是。外包已经成为许多企业的主要战略。因此,我们选择了一家成功部署大数据项目的外包公司作为研究对象。我们分析了10个外包大数据项目的研究结果,为大数据的早期采用者提供了一瞥,阐明了源自大数据5v的系统开发挑战,并明确了架构设计选择和技术选择的重要性。我们遵循协作实践研究(CPR)方法来开发和验证一种称为BDD的新方法。BDD是第一次尝试系统地将架构设计与数据建模方法结合起来,以解决大数据系统开发挑战。参考架构和技术目录的使用是架构设计方法的进步,并且被证明非常适合大数据系统架构设计和系统开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big Data System Development: An Embedded Case Study with a Global Outsourcing Firm
Big data system development is dramatically different from small (traditional, structured) data system development. At the end of 2014, big data deployment is still scarce and failures abound. Outsourcing has become a main strategy for many enterprises. We therefore selected an outsourcing company who has successfully deployed big data projects for our study. Our research results from analyzing 10 outsourced big data projects provide a glimpse into early adopters of big data, illuminates the challenges for system development that stem from the 5Vs of big data and crystallizes the importance of architecture design choices and technology selection. We followed a collaborative practice research (CPR) method to develop and validate a new method, called BDD. BDD is the first attempt to systematically combine architecture design with data modeling approaches to address big data system development challenges. The use of reference architectures and a technology catalog are advancements to architecture design methods and are proving to be well-suited for big data system architecture design and system development.
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