While data scientists have many resources in their tool belt, our research shows that proficiency with data mining and visualization tools consistently ranks as one of the most important skills in determining project success.
We used two methods to rank data science skills. The first way was based on the frequency with which professionals possessed the skills. This method identified data science skills that are common across data scientists. The second way based on the correlation between the data scientists’ proficiency in the skill and project outcome. This method identified data science skills that are linked to project success. Comparing the results using these two ranking methods lead to some interesting conclusions about specific data science skills. Over the next few weeks, I will be exploring specific data science skills and what these findings mean to data scientists and businesses that hire them.
We found that, across all the data professionals we surveyed, the data science skill that had the highest correlation with project success was Data Mining and Visualization Tools. That is, data scientists who were very proficient using these tools were significantly more satisfied with outcome of their work compared to data scientists who were not proficient using these tools.
Even when we examined the data science skills for each of the four data roles (i.e., business, developer, creative, researcher), being proficient in Data Mining and Visualization Tools was ranked among the top five data science skills for each job role (Business: ranked 2; Developers: ranked 4; Creative: ranked 2; Researcher: ranked 2). Figure 1 illustrates the difference between data scientists who are proficient in data mining and visualization tools and those who are not.
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