数据科学路线图:走向架构框架

Kerem Kayabay, M. Gökalp, E. Gökalp, P. Eren, Altan Koçyiğit
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引用次数: 0

摘要

大数据和相关技术的可用性使企业能够利用数据获得竞争优势。尽管如此,许多行业在利用数据科学来克服业务问题时仍面临障碍。本文探讨了解决数据科学挑战的路线图方法的发展。为了实现这一目标,我们通过综合路线图、大数据、数据科学和数据驱动组织文献来定制技术路线图。由此产生的数据科学路线图方法将业务战略与数据相关的、技术的和组织的资源联系起来。它还支持沟通、涉众参与和项目优先级划分。虽然大多数现有研究都说明了预先构建的路线图,但本研究侧重于路线图绘制的过程。应用路线图过程而不是特定的路线图可以提供上述好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Science Roadmapping: Towards an Architectural Framework
The availability of big data and related technologies enables businesses to exploit data for competitive advantage. Still, many industries face obstacles while leveraging data science to overcome business problems. This paper explores the development of a roadmapping approach to address data science challenges. Towards this goal, we customize technology roadmapping by synthesizing roadmapping, big data, data science, and data-driven organization literature. The resulting data science roadmapping approach links business strategy with data-related, technological, and organizational resources. It also enables communication, stakeholder buy-in, and project prioritization. While most of the existing studies illustrate prebuilt roadmaps, this study focuses on the process of roadmapping. The application of the roadmapping process rather than a particular roadmap provides the benefits above.
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