工具箱
分析
数据科学
计算机科学
数据分析
产品(数学)
产品规划
新产品开发
过程管理
业务
数据挖掘
营销
几何学
数学
程序设计语言
作者
Melina Panzner,Sebastian von Enzberg,Roman Dumitrescu
标识
DOI:10.1017/s0890060424000209
摘要
Abstract The application of data analytics to product usage data has the potential to enhance engineering and decision-making in product planning. To achieve this effectively for cyber-physical systems (CPS), it is necessary to possess specialized expertise in technical products, innovation processes, and data analytics. An understanding of the process from domain knowledge to data analysis is of critical importance for the successful completion of projects, even for those without expertise in these areas. In this paper, we set out the foundation for a toolbox for data analytics, which will enable the creation of domain-specific pipelines for product planning. The toolbox includes a morphological box that covers the necessary pipeline components, based on a thorough analysis of literature and practitioner surveys. This comprehensive overview is unique. The toolbox based on it promises to support and enable domain experts and citizen data scientists, enhancing efficiency in product design, speeding up time to market, and shortening innovation cycles.
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