The aim of this paper is to frame Data Science, a fashion and emerging topicnowadays in the context of business and industry. We open with a discussionabout the origin of Data Science and its requirement for a challenging mix ofcapability in data analytics, information technology, and business know-how.The mission of Data Science is to provide new or revised computational theoryable to extract useful information from the massive volumes of data collected atan accelerating pace. In fact, besides the traditional measurements, digital dataobtained from images, text, audio, sensors, etc complement the survey. Then, wereview the different and most popular methodologies among the practitionersof Data Science research and applications. In addition, because the emergingfield requires personnel with new competences, we attempt to describe the DataScientist profile, one of the sexiest jobs of the 21st Century according to Davenportand Patil. Most people are aware of the need to embrace Data Science, but theyfeel intimidated that they do not understand it and they worry that their jobs willdisappear. We want to encourage them: Data Science is more likely to add valueto jobs and enrich the lives of working people by helping them make better, moreinformed business decisions. We conclude this paper by presenting examples ofData Science in action in business and industry, to demonstrate the collection ofspecialist skills that must come together for this new science to be effective.

A review of data science in business and industry and a future view / Vicario, Grazia; Coleman, Shirley. - In: APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY. - ISSN 1526-4025. - ELETTRONICO. - 36:(2019), pp. 6-18. [10.1002/asmb.2488]

A review of data science in business and industry and a future view

Grazia, Vicario;
2019

Abstract

The aim of this paper is to frame Data Science, a fashion and emerging topicnowadays in the context of business and industry. We open with a discussionabout the origin of Data Science and its requirement for a challenging mix ofcapability in data analytics, information technology, and business know-how.The mission of Data Science is to provide new or revised computational theoryable to extract useful information from the massive volumes of data collected atan accelerating pace. In fact, besides the traditional measurements, digital dataobtained from images, text, audio, sensors, etc complement the survey. Then, wereview the different and most popular methodologies among the practitionersof Data Science research and applications. In addition, because the emergingfield requires personnel with new competences, we attempt to describe the DataScientist profile, one of the sexiest jobs of the 21st Century according to Davenportand Patil. Most people are aware of the need to embrace Data Science, but theyfeel intimidated that they do not understand it and they worry that their jobs willdisappear. We want to encourage them: Data Science is more likely to add valueto jobs and enrich the lives of working people by helping them make better, moreinformed business decisions. We conclude this paper by presenting examples ofData Science in action in business and industry, to demonstrate the collection ofspecialist skills that must come together for this new science to be effective.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2831611