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Supporting Analytical Reasoning A Study from the Automotive Industry

机译:支持分析推理的汽车行业研究

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In the era of big data, it is imperative to assist the human analyst in the endeavor to find solutions to ill-defined problems, i.e. to "detect the expected and discover the unexpected" . To their aid, a plethora of analysis support systems is available to the analysts. However, these support systems often lack visual and interactive features, leaving the analysts with no opportunity to guide, influence and even understand the automatic reasoning performed and the data used. Yet, to be able to appropriately support the analysts in their sense-making process, we must look at this process more closely. In this paper, we present the results from interviews performed together with data analysts from the automotive industry where we have investigated how they handle the data, analyze it and make decisions based on the data, outlining directions for the development of analytical support systems within the area.
机译:在大数据时代,当务之急是要帮助人类分析人员寻找解决未定义问题的解决方案,即“发现期望并发现意外事件”。在他们的帮助下,分析人员可以使用大量的分析支持系统。但是,这些支持系统通常缺乏视觉和交互功能,因此分析人员没有机会指导,影响甚至理解执行的自动推理和所使用的数据。但是,为了能够在分析过程中为分析人员提供适当的支持,我们必须更仔细地研究这个过程。在本文中,我们介绍了与汽车行业的数据分析师一起进行的采访所得的结果,我们在调查中调查了他们如何处理数据,对其进行分析并根据这些数据做出决策,并概述了汽车内部分析支持系统的开发方向。区域。

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