Why Data Scientists Don't Have Time to Do Analysis
Data scientists spend too much time cleaning and organizing data, which pulls them away from what they should be doing: conducting business-benefitting analysis, according to a recent survey from CrowdFlower. Being understaffed contributes to the problem, as does a lack of access to required tools and resources like R and Tableau. These professionals would also be better served by a clearer sense of their organization's goals for individual projects, findings show. "Data scientists are valuable to their companies, but there's still a disconnect between what they actually do and what they want to do," says Lukas Biewald, co-founder and CEO of CrowdFlower. "At the end of the day, the time they invest in cleaning data is time that could be better spent doing strategic, creative work like predictive analysis or data mining." Despite the challenges, it's reassuring to find that a large majority of data scientists are happy with their jobs, and quite a few consider what they do "awesome." More than 150 U.S. data scientists took part in the research.