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Facilitating transmuters' acquisition of data scientist knowledge based on their educational backgrounds: state-of-the-practice and challenges
Library Hi Tech Pub Date : 2021-02-19 , DOI: 10.1108/lht-08-2020-0203
Muhammad Javed Ramzan , Saif Ur Rehman Khan , Inayat ur-Rehman , Muhammad Habib Ur Rehman , Ehab Nabiel Al-khannaq

Purpose

In recent years, data science has become a high-demand profession, thereby attracting transmuters (individuals who want to change their profession due to industry trends) to this field. The primary purpose of this paper is to guide transmuters in becoming data scientists.

Design/methodology/approach

An exploratory study was conducted to uncover the challenges faced by data scientists according to their educational backgrounds. An extensive set of responses from 31 countries was received.

Findings

The results reveal that skill requirements and tool usage vary significantly with educational background. However, regardless of differences in academic background, the data scientists surveyed spend more time analyzing data than operationalizing insight.

Research limitations/implications

The collected data are available to support replication in various scenarios, for example, for use as a roadmap for those with an educational background in art-related disciplines. Additional empirical studies can also be conducted specific to geographical location.

Practical implications

The current work has categorized data scientists by their fields of study making it easier for universities and online academies to suggest required knowledge (courses) according to prospective students' educational background.

Originality/value

The conducted study suggests the required knowledge and skills for transmuters to acquire, based on their educational background, and reports a set of motivational factors attracting them to adopt the data science field.



中文翻译:

根据教育背景促进转化者获取数据科学家知识:实践现状和挑战

目的

近年来,数据科学已经成为一个高需求的职业,从而吸引了transmuters(由于行业趋势而想要改变职业的个人)到这个领域。本文的主要目的是指导 Transmuters 成为数据科学家。

设计/方法论/途径

进行了一项探索性研究,以揭示数据科学家根据其教育背景所面临的挑战。我们收到了来自 31 个国家的广泛答复。

发现

结果表明,技能要求和工具使用因教育背景而异。然而,尽管学术背景存在差异,接受调查的数据科学家花在分析数据上的时间多于将洞察力付诸实践的时间。

研究局限性/影响

收集到的数据可用于支持各种场景中的复制,例如,用作具有艺术相关学科教育背景的人员的路线图。还可以针对地理位置进行其他实证研究。

实际影响

目前的工作按数据科学家的研究领域对数据科学家进行了分类,使大学和在线学院更容易根据潜在学生的教育背景建议所需的知识(课程)。

原创性/价值

这项研究根据转化者的教育背景提出了转化者需要获得的知识和技能,并报告了一系列吸引他们进入数据科学领域的动机因素。

更新日期:2021-02-19
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