Data Quality: What if Deming Were Born Today?

IF 1.3 4区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Dennis K. J. Lin, Nicholas Rios
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引用次数: 0

Abstract

If Francis Bacon were born today, he might have said “data is power” instead of his original saying, “knowledge is power.” In modern society, data is everywhere. In memory of Deming (a guru in quality), this paper attempts to address the fundamental issue of data quality and how Deming would handle it. Specifically, we attempt to explain what data quality really means, and the critical impact that it has on data science. Statisticians, who understand how to collect high quality data, have much more to contribute to both the intellectual vitality and the practical utility of data science. At the same time, data science challenges statisticians to move out of some familiar habits to engage less structured problems, to become more comfortable with ambiguity, and to engage more scientists in a fruitful discussion on what various parties can bring to this new mode of investigation. Some potential avenues for future research in the collection of high-quality data will be proposed.

Abstract Image

数据质量:如果戴明出生在今天会怎样?
如果弗朗西斯·培根出生在今天,他可能会说“数据就是力量”,而不是他最初所说的“知识就是力量”。在现代社会,数据无处不在。为了纪念戴明(质量大师),本文试图解决数据质量的基本问题以及戴明将如何处理它。具体来说,我们试图解释数据质量的真正含义,以及它对数据科学的关键影响。统计学家,谁知道如何收集高质量的数据,有更多的贡献,无论是智力活力和数据科学的实际应用。与此同时,数据科学挑战统计学家摆脱一些熟悉的习惯,去处理不那么结构化的问题,更适应模棱两可,并让更多的科学家参与到富有成效的讨论中,讨论各方可以为这种新的调查模式带来什么。本文还将提出未来高质量数据收集研究的一些潜在途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.70
自引率
0.00%
发文量
67
审稿时长
>12 weeks
期刊介绍: ASMBI - Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis) was first published in 1985, publishing contributions in the interface between stochastic modelling, data analysis and their applications in business, finance, insurance, management and production. In 2007 ASMBI became the official journal of the International Society for Business and Industrial Statistics (www.isbis.org). The main objective is to publish papers, both technical and practical, presenting new results which solve real-life problems or have great potential in doing so. Mathematical rigour, innovative stochastic modelling and sound applications are the key ingredients of papers to be published, after a very selective review process. The journal is very open to new ideas, like Data Science and Big Data stemming from problems in business and industry or uncertainty quantification in engineering, as well as more traditional ones, like reliability, quality control, design of experiments, managerial processes, supply chains and inventories, insurance, econometrics, financial modelling (provided the papers are related to real problems). The journal is interested also in papers addressing the effects of business and industrial decisions on the environment, healthcare, social life. State-of-the art computational methods are very welcome as well, when combined with sound applications and innovative models.
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