Data Analytics on Online Labor Markets: Opportunities and Challenges
Abstract
The data-driven economy has led to a significant shortage of data scientists. To address this shortage, this study explores the prospects of outsourcing data analysis tasks to freelancers available on online labor markets (OLMs) by identifying the essential factors for this endeavor. Specifically, we explore the skills required from freelancers, collect information about the skills present on major OLMs, and identify the main hurdles for out-/crowd-sourcing data analysis. Adopting a sequential mixed-method approach, we interviewed 20 data scientists and subsequently surveyed 80 respondents from OLMs. Besides confirming the need for expected skills such as technical/mathematical capabilities, it also identifies less known ones such as domain understanding, an eye for aesthetic data visualization, good communication skills, and a natural understanding of the possibilities/limitations of data analysis in general. Finally, it elucidates obstacles for crowdsourcing like the communication overhead, knowledge gaps, quality assurance, and data confidentiality, which need to be mitigated.
Keywords
Cite
@article{arxiv.1707.01790,
title = {Data Analytics on Online Labor Markets: Opportunities and Challenges},
author = {Michael Feldman and Frida Juldaschewa and Abraham Bernstein},
journal= {arXiv preprint arXiv:1707.01790},
year = {2017}
}