Data analysts who learn open source software programs such as R, Phython and Hadoop can earn a higher salary, according to a survey conducted by O’Reilly Strata.
The 2013 Data Science Salary Survey gathered information from the attendees of the Strata Conference: Making Data Work in Santa Clara, Calif., and Strata + Hadoop World in New York. Responses came from 37 U.S. states and 33 countries.
The survey found that employees who use more tools have higher salaries on average. The median base salary remains constant at $100,000 for those able to use up to 10 tools, but the salary increases as the number of tools increases, with a median salary of $130,000 for those who know 15 tools and more.
Employees who use open source tools like Hadoop also tend to use more data analysis tools overall and thus have a higher salary on average, the survey found. Open source software shares the common feature of allowing access and supporting analysis of large data sets.
Big Data has become increasingly relevant in the past few years with the rise in popularity of applications using huge data sets, such as apps for finding parking spaces in a big city or pollution data for different regions.
O’Reilly Media data analyst John King and O’Reilly Media research director Roger Magoulas, who authored the report, concluded, "until the supply of such analysts [able to work with large datasets] catches up, their salaries will naturally be bid up."
The most commonly used data tool is the commercial software SQL, with 42 percent of data workers and 29 percent of non-data workers (like managers or executives) using the tool. In second and third place are the open-source platforms R and Python with Excel just behind. The traditional statistical programs SAS and SPSS now trail in last place.
One of the more surprising findings was that early start-ups gave data workers the highest median salary of $130,000. Meanwhile public companies offered a median salary of $110,000, private companies $100,000 and government and education organizations paid $80,000.
