ABSTRACT

The tremendous amount of data collected from connected devices and social media has created a high demand for new skills to help organizations gain the power of big data. With a shorter completion time, graduate certificates appeared to be a desirable alternative for working professionals to develop these skills. However, it was unclear if graduate certificates met the job market’s needs. Quantitative text analysis was used to analyze data science skills in more than 5,000 data science job descriptions and skills taught in 588 required courses in 166 graduate certificates to investigate if skills needed in the industry were taught in these graduate certificates. The results showed that 21% of skills were common across seven job categories. ‘Team’ was a non-technical skill in high demand, while ‘Python’ and ‘SQL’ were the technical skills in high demand. Although Business offered the highest number of certificates, a lower number of data-science skills were taught in these certificates. The findings also suggested that job categories in the EDISON Data Science Professional Profiles could be grouped into two separate profile groups. The findings of this research provide a comprehensive list of skills that are common in a wide range of data science jobs for universities to consider while they develop their data science programs.

摘要

从连接的设备和社交媒体收集的大量数据对帮助组织获得大数据力量的新技能提出了很高的需求。由于完成时间较短，研究生证书似乎是在职专业人士发展这些技能的理想选择。然而，尚不清楚研究生证书是否满足就业市场的需求。定量文本分析用于分析 5,000 多个数据科学职位描述中的数据科学技能和 166 个研究生证书的 588 门必修课程中教授的技能，以调查这些研究生证书中是否教授了行业所需的技能。结果显示，21% 的技能在七个工作类别中是通用的。“团队”是一种需求量很大的非技术技能，而“Python”和“SQL”是高需求的技术技能。尽管商业提供的证书数量最多，但这些证书中教授的数据科学技能数量较少。调查结果还表明，爱迪生数据科学专业档案中的工作类别可以分为两个独立的档案组。这项研究的结果提供了一份全面的技能列表，这些技能在各种数据科学工作中都很常见，供大学在开发数据科学项目时考虑。