We surveyed 11,699 data analysts to better understand the work environment and required skills of a typical data analyst. Here are the results.
How much intelligence is required as a data analyst?
Low
High
Working as a data analyst typically requires higher levels of intelligence when compared with the average career. This means that data analysts are required to actively learn new things related to their discipline and solve complex problems.
Can I learn to become a data analyst?
Intrinsic Talent
Acquired Talent
A career as a data analyst typically depends predominantly on qualities you’re born with, with a small aspect of skills you can learn.
Is it easy to get a job as a data analyst?
Easy
Hard
It’s typically difficult to find a job as a data analyst.
Do data analysts work full-time or part-time?
85% of data analysts work in full-time roles while 15% work part-time.
Is being a data analyst stressful?
Low
High
Data analysts tend not to find their jobs stressful, which likely contributes positively to career satisfaction.
Is being organized important as a data analyst?
Low
High
Organization is considered a very important trait for data analysts, and is critical to success in the field.
How competitive is the workplace for data analysts?
Low
High
Data analysts see mild competition in their workplace.
Does being a data analyst require frequent time pressure to complete tasks?
Low
High
Data analysts will have to sometimes face time pressure on the job.
Are data analysts allowed to express themselves creatively?
Low
High
Data analysts rarely get a chance to express themselves creatively.
Do data analysts have control over the direction of their work?
Low
High
Data analysts tend to have a set and inflexible work schedule that they are unable to deviate from too much.
Are data analysts exposed to a wide variety of work?
Low
High
Data analysts tend to have a monotonous work routine, with little variety in their day-to-day tasks.
Does being a data analyst require attention to detail?
Low
High
Attention to detail is a vital skill for data analysts, as small mistakes can make or break one's ability to succeed in the career.