Data analytics

I. Shepherd, G. Hearne
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引用次数: 0

Abstract

Data analytics have emerged in recent years as a family of overlapping, competing and hybridising products and practices. They have been championed by technology companies, academics, business users and governments alike, and in a short period of time have earned business developers and adopters billions of pounds in revenue and unprecedented levels of market domination. Data analytics have also provided distinct benefits in terms of an increasing democratisation of digital tools, but at the same time are giving rise to increasing levels of societal and governmental concern. This chapter has four aims: to help intelligent outsiders and old school data analysts make sense of the many competing methodologies and technologies that inhabit the data analytics ecosystem; to assist readers understand which of the many techniques and methodologies represent genuine additions to the state of the art rather than simply old wine in new bottles; to provide a brief overview of the software tools currently available for data analytics; and to identify societal issues and concerns that attend this family of technical and social practices, and the extent to which they are being adequately addressed by developers, users and society at large.
数据分析
近年来,数据分析作为一系列重叠、竞争和混合的产品和实践出现。它们得到了科技公司、学者、商业用户和政府的支持,并在短时间内为商业开发者和采用者带来了数十亿英镑的收入和前所未有的市场支配地位。数据分析在数字工具的日益民主化方面也提供了明显的好处,但同时也引起了社会和政府越来越多的关注。本章有四个目标:帮助聪明的外部人士和老派数据分析师理解数据分析生态系统中许多相互竞争的方法和技术;帮助读者了解哪些技术和方法代表了真正的艺术状态的补充,而不是简单的新瓶装旧酒;简要介绍当前可用的数据分析软件工具;并确定参与该技术和社会实践家族的社会问题和关注点,以及开发人员、用户和整个社会正在充分解决这些问题的程度。
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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