Why Data Scientists Don't Have Time to Do Analysis
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Off-Balance
67% of the data scientists surveyed said cleaning and organizing data is among their most time-consuming tasks, and 40% said they don't have enough time to do analysis. -
Short Handed
Nearly 80% said there's a lack of data scientists available to gather, clean and enrich data to drive better business decision making. -
Biggest Challenges for Data Scientists
Too much time spent cleaning data: 58%, Poor quality of data: 52%, Insufficient time to do analysis: 40%, Limited ability to model collected data effectively: 30%, Limitations of available tech and tools: 30% -
Ways Business Can Empower Data Scientists
Provide all tools necessary to do the job effectively: 54%, Set clearer goals and objectives on projects: 52%, Invest more in training and development: 48%, Allow for realistic timing to complete projects: 41%, Increase headcount on the data science team: 24% -
Happy Campers
Nearly 79% of data scientists surveyed are satisfied with their jobs, and 30% said it's "totally awesome." -
What Makes Data Scientists Happy at Work
Performing predictive analysis: 54%, Mining data for patterns: 52%, Interacting with data dynamically: 50% -
Top Data Science Tools
Excel: 56%, R: 43%, Tableau: 26% -
Top Roles of Data Scientists
Researcher: 54%, Computer scientist: 52%, Business intelligence analyst: 36%, Mathematician: 19% -
Top Career Success Drivers
Working with a diverse portfolio of problems: 59%, Interacting with others in the field as much as possible: 57%, Working with a broad range of languages and platforms: 53%, Increasing business acumen, not just data science skills: 50% -
Minor Degree of Distinction
Only 22% said you need a master's or doctoral degree to advance in this career.
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. 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.