Data Analytics on Online Labor Markets: Opportunities and Challenges

TL;DR

This paper investigates the potential of outsourcing data analysis tasks to freelancers on online labor markets, identifying essential skills and challenges to facilitate effective crowd-sourced data analytics.

Contribution

It provides a comprehensive analysis of the skills needed and hurdles faced in outsourcing data analysis to online freelancers, based on interviews and surveys.

Findings

Freelancers require technical, domain, visualization, and communication skills.

Main obstacles include communication overhead, quality assurance, and data confidentiality.

Essential skills extend beyond technical expertise to include understanding data analysis limitations.

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.